MCP Server for Z.AI - A Model Context Protocol server that provides AI capabilities
Nothing to run from here
Control Plane is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
68
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
Enterprise AI governance: spend, guardrails, policy, budgets, compliance, and provider health.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http control-plane-mcp https://mcp.thinkneo.ai/mcp
# 2 — ask your agent for something these tools do
# thinkneo_check_spend, thinkneo_complete, thinkneo_read_memory and 65 more
Control Plane costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
MTAll 1 server
mcp.thinkneo.ai1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http control-plane-mcp https://mcp.thinkneo.ai/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
68 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Check AI spend summary for a workspace, team, or project. Returns real cost breakdown by provider, model, and time period from the ThinkNEO AI gateway.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace name or ID |
| period | string | no | Time period: today, this-week, this-month, last-month |
| group_by | string | no | Group costs by: provider, model, team, or project |
Run a governed LLM completion through the ThinkNEO AI gateway. The request is authorized, classified, and policy-checked against your workspace governance BEFORE any provider is called — a blocked prompt never reaches the model. Tenant/workspace are derived from your API key.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| prompt | string | yes | The user prompt to complete |
| model | string | no | provider/model, e.g. 'anthropic/claude-haiku-4-5-20251001' |
| system | no | Optional system instruction | |
| max_tokens | integer | no | Max output tokens |
| temperature | number | no | Sampling temperature |
Read Claude Code project memory files. Without arguments, returns the MEMORY.md index listing all available memories. With a filename argument, returns the full content of that specific memory file. Use this to access project context, user preferences, feedback, and reference notes persisted across Claude Code sessions.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| filename | no | Name of the memory file to read (e.g. 'user_fabio.md', 'project_thinkneodo_droplet.md'). Omit to get the MEMORY.md index with all available files. |
Write or update a Claude Code project memory file (.md). Persists project context, user preferences, feedback, and reference notes across Claude Code sessions. Filename must end in .md with lowercase alphanumeric characters. Path traversal is blocked. Requires authentication.Use this to persist project context, user preferences, feedback, and reference notes across Claude Code sessions. The filena
| Parameter | Type | Required | Notes |
|---|---|---|---|
| filename | string | yes | Name of the memory file to write (e.g. 'user_fabio.md', 'project_thinkneodo_droplet.md'). Must end in .md. |
| content | string | yes | Full markdown content to write to the file. |
Evaluate a prompt or text against ThinkNEO guardrail policies before sending it to an AI provider. Returns risk assessment, violations found, and recommendations. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | The prompt or text content to evaluate for policy violations (max 32,000 characters) |
| workspace | string | yes | Workspace whose guardrail policies to apply for this evaluation |
| guardrail_mode | string | no | Evaluation mode: 'monitor' (log violations only) or 'enforce' (block the request on violation) |
Free-tier prompt safety check. Analyzes text for prompt injection patterns and PII (credit card numbers, Brazilian CPF, US SSN, email, phone, passwords). Returns a safety assessment with specific warnings. No authentication required.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | The text or prompt to check for safety issues (max 50,000 characters) |
Check AI governance policies including model access, budget limits, data controls, and agent governance from the ThinkNEO gateway.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace name or ID |
Check AI budget status including spend vs limit, forecast, and chargeback data from the ThinkNEO gateway.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace name or ID |
List active alerts for budget, policy, SLA, and security from the ThinkNEO gateway.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace name or ID |
| severity | string | no | Filter by severity: critical, high, medium, low, all |
Get compliance status including framework coverage (EU AI Act, ISO 42001, NIST AI RMF, SOC 2) and governance assessments from the ThinkNEO gateway.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace name or ID |
| framework | string | no | Filter by framework: eu-ai-act, iso-42001, nist-ai-rmf, soc2, all |
Get real-time health and performance status of AI providers routed through the ThinkNEO gateway. Shows latency, error rates, and availability. No authentication required.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| provider | no | Specific provider to check: openai, anthropic, google, mistral, xai, cohere, or together. Omit to get status for all providers. | |
| workspace | no | Workspace context for provider routing configuration (optional) |
Schedule a demo or discovery call with the ThinkNEO team. Collects contact information and preferences. No authentication required.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| contact_name | string | yes | Full name of the person requesting the demo |
| company | string | yes | Company or organization name |
| string | yes | Business email address to receive follow-up from the ThinkNEO team | |
| role | no | Contact's role: cto, cfo, security, engineering, or other | |
| interest | no | Primary area of interest: guardrails, finops, observability, governance, or full platform | |
| preferred_dates | no | Preferred meeting dates, times, and timezone (e.g., 'Tuesdays or Thursdays, 9-11am EST') | |
| context | no | Additional context such as current AI providers used, request volume, or specific use case |
Returns usage statistics for your ThinkNEO API key. Shows calls today, this week, this month, monthly limit, remaining calls, top tools used, estimated cost, and current tier. Works without authentication (returns general info).
No parameter schema on file.
AI Smart Router — find the cheapest model that meets your quality threshold. Specify your task type and quality requirements, and ThinkNEO will recommend the optimal model with estimated cost and savings vs premium models. Supports 17+ models across Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, Alibaba, Cohere, and xAI. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| task_type | string | yes | The type of AI task: summarization, classification, code_generation, chat, analysis, translation, or embedding |
| quality_threshold | integer | no | Minimum quality score required (0-100). Default 85 = enterprise-grade. |
| max_latency_ms | no | Maximum acceptable latency in milliseconds. Omit for no limit. | |
| budget_per_request | no | Maximum budget per request in USD. Omit for no limit. | |
| preferred_providers | no | Comma-separated list of preferred providers (e.g., 'openai,anthropic'). These will be prioritized at similar cost. | |
| estimated_tokens | integer | no | Estimated total tokens for the request (input + output). Default 1000. |
| text_sample | no | Optional sample text for better routing. Helps estimate token count and task complexity. Max 500 characters. |
Get your AI cost savings report. Shows total requests routed, original cost (what you'd have paid with premium models), actual cost, total savings, savings percentage, breakdown by task type, and model distribution. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| period | string | no | Report period: '7d' (7 days), '30d' (30 days), or '90d' (90 days) |
Simulate how much your organization would save on AI costs using ThinkNEO Smart Router. Enter your current monthly AI spend and primary model, and see estimated monthly and annual savings with a recommended model mix. No authentication required — try it now!
| Parameter | Type | Required | Notes |
|---|---|---|---|
| monthly_ai_spend | number | yes | Your current monthly AI API spend in USD (e.g., 5000.00) |
| primary_model | string | no | Your primary model: 'gpt-4o', 'claude-opus-4', 'claude-sonnet-4', 'gpt-4.1', or 'gemini-2.5-pro' |
| task_distribution | no | JSON string of task distribution, e.g., '{"chat": 0.3, "summarization": 0.2, "code_generation": 0.2, "classification": 0.15, "analysis": 0.1, "translation": 0.05}'. Values should sum to ~1.0. Omit for |
Evaluate your organization AI Trust Score (0-100) across 10 dimensions: Guardrails, PII Protection, Injection Defense, Audit Trail, Compliance, Model Governance, Cost Controls, Outcome Validation, Observability, and Smart Routing. Returns a score, detailed breakdown, badge level (Platinum/Gold/Silver/Bronze/Unrated), and actionable recommendations. Score is valid for 30 days. Generates a public ba
| Parameter | Type | Required | Notes |
|---|---|---|---|
| org_name | string | yes | Organization name for the trust score badge (e.g., 'Acme Corp') |
Get a public AI Trust Score badge by report token. Returns the organization name, score, badge level, and validity period. Use the badge URL to embed the trust badge in websites and documentation. No authentication required.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| report_token | string | yes | The report token from a trust score evaluation (URL-safe string) |
Search the ThinkNEO MCP Marketplace — the npm for MCP tools. Discover MCP servers and tools by keyword, category, rating, or verified status. Returns name, description, tools count, rating, downloads, and verified badge. No authentication required.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| query | string | no | Search query — matches name, description, tags, and tool names |
| category | no | Filter by category: governance, security, data, development, productivity, communication, analytics, devops, finance, marketing, other | |
| min_rating | no | Minimum average rating (1.0-5.0) | |
| verified_only | boolean | no | If true, return only verified packages |
| limit | integer | no | Max results to return (1-100, default 20) |
Get full details for an MCP server package from the ThinkNEO Marketplace. Returns readme, full tools list, version history, reviews, security score, and installation instructions. No authentication required.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| name | string | yes | Package name (e.g. 'thinkneo-control-plane', 'filesystem', 'github') |
Publish an MCP server to the ThinkNEO Marketplace. Validates the endpoint by calling initialize and tools/list, runs automated security scan for secrets and injection patterns, computes a security score (0-100), and stores the entry with version history. Validates the endpoint (calls initialize + tools/list), runs security scan (secrets detection, injection patterns), and stores the entry. Authent
| Parameter | Type | Required | Notes |
|---|---|---|---|
| name | string | yes | Package name (lowercase, hyphens allowed, e.g. 'my-mcp-server') |
| display_name | string | yes | Human-readable display name |
| description | string | yes | Short description of what this MCP server does (max 500 chars) |
| endpoint_url | string | yes | MCP server endpoint URL (e.g. https://my-server.com/mcp) |
| transport | string | no | Transport type: streamable-http, sse, or stdio |
| categories | no | Categories: governance, security, data, development, productivity, communication, analytics, devops, finance, marketing, other | |
| tags | no | Tags for discoverability (e.g. ['ai', 'governance', 'security']) | |
| repo_url | string | no | Source code repository URL |
| license | string | no | License (e.g. MIT, Apache-2.0) |
| readme | string | no | Full readme/documentation in markdown |
Rate and review an MCP server in the ThinkNEO Marketplace. One review per user per package (updates on repeat). Rating from 1 (poor) to 5 (excellent) with optional comment. Reviews affect the package average rating shown in search results. One review per user per package (updates on repeat). Authentication required.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| name | string | yes | Package name to review |
| rating | integer | yes | Rating from 1 (poor) to 5 (excellent) |
| comment | string | no | Review comment (max 2000 chars) |
Get installation config for an MCP server from the ThinkNEO Marketplace. Returns ready-to-use JSON config for Claude Desktop, Cursor, Windsurf, or custom clients. Tracks the download. No authentication required.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| name | string | yes | Package name to install (e.g. 'thinkneo-control-plane') |
| client_type | string | no | Your MCP client: claude-desktop, cursor, windsurf, or custom |
Bridge MCP tool registry to A2A format. Shows tool-to-skill mappings.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| tool_name | string | no | MCP tool name to bridge |
Bridge A2A agents to MCP tool format.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| agent_name | string | no | A2A agent name to map |
Generate an A2A Agent Card from registry data.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| agent_id | string | yes | Agent ID from registry |
List all MCP <-> A2A bridge mappings for a tenant.
No parameter schema on file.
Start a new agent observability trace. Creates a session that tracks all tool calls, model calls, decisions, and errors for an AI agent run. Returns a session_id to use with thinkneo_log_event and thinkneo_end_trace. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| agent_name | string | yes | Name of the agent being traced (e.g., 'marketing-agent', 'support-bot') |
| agent_type | string | no | Type of agent: 'assistant', 'autonomous', 'workflow', 'pipeline', or 'generic' |
| metadata | no | Optional dict with additional context (e.g., {"task": "email-draft", "user_id": "u123"}) |
Log an event within an active agent trace. Supports event types: tool_call, model_call, decision, error, pii_access, guardrail_triggered. Returns event_id and running session cost. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| session_id | string | yes | Session ID from thinkneo_start_trace |
| event_type | string | yes | Event type: 'tool_call', 'model_call', 'decision', 'error', 'pii_access', or 'guardrail_triggered' |
| tool_name | no | Name of the tool called (for tool_call events) | |
| model_name | no | Model used (for model_call events, e.g., 'gpt-4o', 'claude-sonnet-4-20250514') | |
| input_summary | no | Brief summary of the input (max 500 chars, truncated if longer) | |
| output_summary | no | Brief summary of the output (max 500 chars, truncated if longer) | |
| cost | number | no | Estimated cost in USD for this event (e.g., 0.003 for an API call) |
| latency_ms | integer | no | Latency in milliseconds for this event |
| metadata | no | Optional dict with additional event context |
End an active agent trace and get the session summary. Returns total cost, duration, tool/model call counts, and event count. Triggers post-session anomaly detection (cost spikes, error rate). Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| session_id | string | yes | Session ID from thinkneo_start_trace |
| status | string | no | Final session status: 'success', 'failure', or 'timeout' |
Retrieve the full trace for an agent session. Returns the complete timeline of events (tool calls, model calls, decisions, errors), session metadata, total cost, duration, and any alerts triggered. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| session_id | string | yes | Session ID to retrieve the trace for |
Get the agent observability dashboard — aggregated metrics for your AI agents. Includes total sessions, events, cost, error rate, latency, top agents, top tools, active alerts, and cost trend over time. Like Datadog, but for AI agents. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| period | string | no | Time period: '1h', '24h', '7d', or '30d' |
Define the pre-AI cost baseline for a business process. Example: 'customer_support_ticket costs $12 per ticket and takes 15 minutes without AI'. This baseline is used to calculate ROI when agents handle the same process. Call this once per process to establish the comparison point.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| process_name | string | yes | Name of the business process, e.g. 'customer_support_ticket', 'loan_review', 'content_moderation' |
| cost_per_unit_usd | number | yes | Pre-AI cost per unit in USD, e.g. 12.00 for a $12 support ticket |
| unit_label | string | no | What one unit represents, e.g. 'ticket', 'review', 'decision', 'document' |
| avg_duration_minutes | no | Average time in minutes for one unit without AI, e.g. 15 | |
| workspace | string | no | Workspace identifier |
| notes | no | Additional context about this baseline |
Log a business decision made by an AI agent. Tracks the AI cost and the business value generated. If a baseline exists for the process, value is auto-calculated from the baseline cost. Example: agent 'support-bot' resolved a 'customer_support_ticket' at $0.03 AI cost, replacing a $12 human-handled ticket. ROI: 400:1.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| agent_name | string | yes | Name of the AI agent that made the decision, e.g. 'support-bot', 'loan-reviewer' |
| decision_type | string | yes | Type of decision, e.g. 'ticket_resolved', 'loan_approved', 'content_reviewed' |
| ai_cost_usd | number | no | Actual AI cost for this decision in USD, e.g. 0.03 |
| process_name | no | Links to a baseline process for auto ROI calculation | |
| value_generated_usd | no | Explicit business value in USD. If omitted and process_name has a baseline, auto-calculated. | |
| outcome | string | no | Result: 'success', 'escalated', 'rejected', 'error' |
| confidence | no | Confidence score 0.0-1.0 | |
| workspace | string | no | Workspace identifier |
| metadata | no | JSON string with additional context |
Log a risk event that was blocked or avoided by the governance layer. Quantifies the estimated dollar impact of the avoided risk. Examples: PII leak blocked (est. $50K GDPR fine), prompt injection prevented, policy violation caught before production. If estimated_impact_usd is not provided, a default is calculated from severity.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| risk_type | string | yes | Type: 'pii_leak', 'injection_blocked', 'policy_violation', 'spend_limit', 'compliance_breach', 'data_exfiltration' |
| severity | string | no | Severity level: 'low', 'medium', 'high', 'critical' |
| estimated_impact_usd | no | Estimated cost if this risk had materialized in USD | |
| agent_name | no | Agent involved, if applicable | |
| description | no | Brief description of what was blocked | |
| workspace | string | no | Workspace identifier |
Analyze cost-per-decision for AI agents. Shows the actual AI cost for each decision, compared to the pre-AI baseline. Answers: 'How much does each AI decision cost?' and 'How does it compare to doing it without AI?'
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
| agent_name | no | Filter by specific agent | |
| process_name | no | Filter by specific process | |
| period | string | no | Time period: 'today', 'this-week', 'this-month', 'all' |
Calculate ROI per AI agent. Shows value generated vs AI cost consumed, with daily trend, success rate, and comparison to pre-AI baseline. Answers: 'Is this agent generating or consuming value?' and 'What's the ROI trend?'
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
| agent_name | no | Specific agent to analyze. If omitted, returns all agents. | |
| days | integer | no | Number of days to analyze |
Executive business impact dashboard. Returns a single view of: total value generated by AI agents, total AI cost, net ROI, risk avoided in dollars, cost per decision, top performing agents, and risk event summary. This is the report a CxO needs to justify AI investment.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
| period | string | no | Time period: 'this-week', 'this-month', 'this-quarter', 'all' |
Retrieve A2A (agent-to-agent) interaction logs from the live gateway. Shows which agents called which, actions performed, costs, and outcomes.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
| limit | integer | no | Max events to return |
Retrieve A2A interaction policies from the live gateway. Shows allowed actions, rate limits, cost caps, and approval requirements.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
Visualize agent-to-agent communication flow. Shows registered agents, their approval status, and interaction patterns from the live gateway.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
Retrieve immutable audit trail for A2A interactions with hash verification. Each event is cryptographically chained for tamper detection.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
| trace_id | no | Filter by trace ID |
Detect waste and inefficiency in AI operations. Analyzes agent performance, A2A communication overhead, error costs, unused capacity, and cost outliers. Returns specific actionable findings like 'you are losing $3,200/month on error retries' or 'this flow is 5x more expensive than your best-performing flow'. This is the diagnostic tool that creates the buying trigger.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
| days | integer | no | Analysis window in days |
Register an action claim from an AI agent. The agent declares it performed an action (e.g., sent an email, created a PR, wrote a file) and ThinkNEO will verify it actually happened. Returns a claim_id for tracking. Part of the Outcome Validation Loop — 'From Prompt to Proof'. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| action | string | yes | Type of action claimed: 'email_sent', 'http_request', 'file_written', 'db_insert', 'pr_created', 'payment_processed', 'message_sent', 'api_call', 'task_completed', 'data_exported', 'notification_sent' |
| target | string | yes | Target of the action — what was acted upon. Examples: 'user@example.com' (email), 'https://api.example.com/endpoint' (http), '/opt/data/report.pdf' (file), 'usage_log' (db table) |
| evidence_type | string | yes | How to verify the claim: 'http_status' (check URL response), 'file_exists' (check file path), 'db_row_exists' (check database row), 'webhook' (wait for callback), 'smtp_delivery' (check email delivery |
| agent_name | no | Name of the agent making the claim (e.g., 'marketing-agent') | |
| session_id | no | Optional observability session_id to link this claim to a trace | |
| metadata | no | Optional verification context. For http_status: {expected_status: 200, method: 'GET'}. For file_exists: {expected_hash: 'sha256...'}. For db_row_exists: {where_column: 'id', where_value: '123'}. | |
| ttl_hours | integer | no | Hours until claim expires if not verified (default 24, max 168) |
Trigger verification of a registered action claim. Runs the appropriate verification adapter (HTTP check, file check, database check, etc.) and returns the result with evidence. If already verified, returns cached result (use force=true to re-verify). Part of the Outcome Validation Loop — 'From Prompt to Proof'. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| claim_id | string | yes | UUID of the claim to verify (from thinkneo_register_claim) |
| force | boolean | no | Force re-verification even if already verified/failed |
Retrieve the immutable proof record for a verified claim. Includes the original claim, verification evidence, verifier identity, and a SHA-256 proof hash for tamper detection. This is the 'proof' in 'From Prompt to Proof'. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| claim_id | string | yes | UUID of the claim to get proof for |
Aggregated outcome verification metrics — verification rates, failure patterns, agent reliability rankings, and daily trends. Shows how reliably your AI agents are delivering verified outcomes. 'Datadog for AI outcomes'. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| period | string | no | Time period: '24h', '7d', or '30d' |
View the outcome benchmark matrix — real quality scores per provider/model/task_type based on verified outcomes, not static estimates. Shows verification rates, sample counts, and rankings. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| task_type | no | Filter by task type: 'summarization', 'code_generation', 'classification', 'translation', etc. Leave empty for all. |
Compare providers side-by-side for a specific task type. Shows quality scores, verification rates, and rankings based on real outcomes. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| task_type | string | yes | Task type to compare: 'summarization', 'code_generation', 'classification', 'translation', 'analysis', 'chat' |
| providers | no | Optional list of providers to compare (e.g., ['anthropic', 'openai']). Leave empty for all. |
Explain why the Smart Router would choose a specific model for a task type. Shows both benchmark-based (real outcomes) and static quality estimates, and explains the reasoning behind the recommendation. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| task_type | string | yes | Task type: 'summarization', 'code_generation', 'classification', 'translation', 'analysis', 'chat' |
| quality_threshold | integer | no | Minimum quality score required (0-100, default 85) |
Generate a compliance report for regulatory frameworks (EU AI Act, ISO 42001, SOC2, NIST). Exports from live audit data.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
| format | string | no | Output format: ndjson or csv |
| framework | string | no | Framework: eu-ai-act, iso-42001, soc2, nist |
Define or update an SLA (Service Level Agreement) for an AI agent. Set accuracy, quality, cost, safety, or latency thresholds with automatic breach detection and configurable actions (alert, escalate, disable, switch_model). Like SRE SLOs but for AI agent outcomes. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| agent_name | string | yes | Agent name to set SLA for (e.g., 'support-bot', 'finance-agent') |
| metric | string | yes | Metric to monitor: 'accuracy' (outcome verification rate %), 'response_quality' (avg quality score), 'cost_efficiency' (cost per verified outcome), 'safety' (guardrail pass rate %), 'latency' (avg res |
| threshold | number | yes | Target threshold value (e.g., 95.0 for 95% accuracy) |
| window | string | no | Rolling window: '1h', '24h', '7d', or '30d' |
| breach_action | string | no | Action on breach: 'alert' (notify), 'escalate' (notify + flag), 'disable' (stop agent), 'switch_model' (fallback model) |
| threshold_direction | string | no | 'min' = actual must be >= threshold (for accuracy, quality). 'max' = actual must be <= threshold (for cost, latency). |
Check current SLA status for all agents or a specific agent. Shows actual metric values vs thresholds, healthy/breached status, and error budget remaining. Automatically records breaches. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| agent_name | no | Optional: specific agent name. Leave empty for all agents. |
View SLA breach history — which SLAs were breached, by which agents, actual vs threshold values, and resolution status. Requires authentication.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| days | integer | no | Days to look back (default 30) |
| agent_name | no | Filter by agent name |
SLA overview dashboard — all agents, current status, error budgets, and recent breaches (7d). The SRE dashboard for AI agents. Requires authentication.
No parameter schema on file.
Export audit events from the live gateway. Supports JSON and CSV formats with date range filtering for SIEM integration.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace identifier |
| format | string | no | Output format: ndjson or csv |
| start_date | no | Start date ISO format | |
| end_date | no | End date ISO format |
Compare available AI models from the live gateway catalog.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| models | string | yes | Comma-separated model IDs to compare (e.g. gpt-4o,claude-sonnet-4-20250514,gemini-2.5-flash) |
Estimate token count for text (chars/4 approximation).
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text to estimate tokens for |
Analyze prompt and suggest optimizations with live metrics context.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| prompt | string | yes | Prompt text to analyze |
Instruct the gateway to rotate an API key.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| key_prefix | string | yes | First 8 chars of the key to rotate |
Check connector grants and secrets status from the gateway.
No parameter schema on file.
Get semantic cache stats from the live gateway runtime metrics.
No parameter schema on file.
Detect prompt injection attempts in text using guardrail patterns. Also retrieves live guardrails_blocked stats from the gateway.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text to analyze for injection attempts |
Detect international PII across 30+ document types from 15+ countries: Brazil (CPF, CNPJ, RG, PIS), USA (SSN, EIN, ITIN, Passport), UK (NINO, UTR), Canada (SIN), EU (IBAN, VAT), Germany (Tax-ID), France (INSEE), Spain (DNI/NIE), Italy (Codice Fiscale), Argentina (CUIT), Mexico (CURP/RFC), Australia (TFN/ABN), India (Aadhaar/PAN), China (ID), Japan (My Number), and credit cards (Luhn validated). Re
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text to scan for PII (max 100,000 chars) |
| countries | array | no | Filter by country codes (BR, US, UK, CA, EU, DE, FR, ES, IT, AR, MX, AU, IN, CN, JP, INTL). Empty = all. |
List your configurable Monitor Agent alert rules. Each rule watches a metric (e.g. an API key reaching a % of its budget, workspace spend, error rate) and notifies your channels (email/discord/whatsapp) when it fires. Requires an admin API key.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| workspace | string | no | Workspace id (optional — defaults to the API key's workspace) |
Create a Monitor Agent alert rule. Example: notify by email when API key 'X' reaches 75% of its budget → metric=key_spend_pct_of_budget, operator=gte, threshold=75, scope_value=<api_key_id>, budget_usd=<key budget>. Requires an admin API key.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| name | string | yes | Human-readable rule name |
| metric | string | yes | One of: key_spend_24h_usd, key_spend_30d_usd, key_spend_pct_of_budget, workspace_error_rate_pct, workspace_max_rps, workspace_requests, workspace_spend_24h_usd, workspace_spend_30d_usd |
| threshold | number | yes | Threshold value to compare the metric against |
| operator | string | no | Comparison: gte, gt, lte, lt, eq |
| scope_value | string | no | API key id — required for key_* metrics |
| budget_usd | number | no | Key budget in USD — required for key_spend_pct_of_budget |
| severity | string | no | low, medium, high, critical |
| channels | string | no | Comma-separated: email, discord_webhook, whatsapp |
| cooldown_minutes | integer | no | Minimum minutes between firings |
| workspace | string | no | Workspace id (optional — defaults to the API key's workspace) |
Delete a Monitor Agent alert rule by its rule_id. Requires an admin API key.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| rule_id | string | yes | The rule_id to delete (from thinkneo_alert_rule_list) |
| workspace | string | no | Workspace id (optional — defaults to the API key's workspace) |
Send a test notification through a rule's configured channels to confirm delivery (email/discord/whatsapp). Requires an admin API key.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| rule_id | string | yes | The rule_id to test (from thinkneo_alert_rule_list) |
| workspace | string | no | Workspace id (optional — defaults to the API key's workspace) |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Control Plane or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
—
Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.28.0.
1.28.0
undated
latestNo release note was published with this version.
—
no reviews yet
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