Chroma’s official MCP server: vector search and collection management for RAG workflows.
Nothing to run from here
Ainative Zerodb 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.
93/100
trust score
27
downloads a day
local
runs on your machine
2k
downloads in 30d
What it does
AINative ZeroDB MCP Server - 77 operations for vector search, TurboQuant vector compression (PolarQuant + QJL), NoSQL, dedicated PostgreSQL management, files, events, RLHF, and persistent memory for AI agents with enterprise security. All tools annotated
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user ainative-zerodb-mcp '--' npx -y ainative-zerodb-mcp-server
# 2 — ask your agent for something these tools do
# zerodb_generate_embeddings, zerodb_embed_and_store, zerodb_semantic_search and 82 more
Ainative Zerodb costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
ASAll 9 servers
ainative-studio9 servers
6 categories
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. This one runs on your machine: your client starts Ainative Zerodb as a process under your own user, with your files and your network, so the tool surface below is what it can do to your computer rather than to a server somewhere else. Its scan result is on the Security tab — read the surface before you approve it.
Claude Codedeclared by this listing
This is a public server: you run it yourself and this marketplace is not in the path. You need Node.js — the current LTS (24) is the safe choice; npx comes with it. Claude Code registers it in one command; --scope user makes it available in every project. The '--' is in quotes so that PowerShell passes it on.
claude mcp add --scope user ainative-zerodb-mcp '--' npx -y ainative-zerodb-mcp-serverReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it runs from its publisher’s own package: 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 your client uses to start the process locally. A local server runs with your file system and your network, which is why it is priced without metering.
What you approve
85 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.
Generate embeddings using specified model (384/768/1024 dimensions). Supports BAAI/bge-small-en-v1.5 (384-dim, default), BAAI/bge-base-en-v1.5 (768-dim), BAAI/bge-large-en-v1.5 (1024-dim). Use when you need raw embedding vectors without storing them. Does not persist data — for embed + store in…
No parameter schema on file.
Generate embeddings and store in ZeroDB in one step. Auto-detects dimension based on model and routes to correct storage. Use when you want to embed text and persist the vectors in a single call. Combines zerodb_generate_embeddings + zerodb_upsert_vector.
No parameter schema on file.
Semantic search using text query (auto-embeds query text). Searches vectors in the same dimension as the model used. Use when searching vectors using a text query (auto-embeds the text). Unlike zerodb_search_vectors which requires a raw vector, this accepts plain text. Unlike zerodb_search_memory…
No parameter schema on file.
Store agent memory in ZeroDB for persistent context. Use when the agent needs to persist conversation turns, decisions, or observations for later recall. Stores with role, session, and agent metadata for filtered retrieval.
No parameter schema on file.
Search agent memory using semantic similarity. Use when searching agent conversation memory by natural language. Unlike zerodb_search_vectors which requires a raw vector, and zerodb_semantic_search which searches the general vector store, this searches agent-specific memory entries filtered by…
No parameter schema on file.
Get agent context window for current session. Use when the agent needs to retrieve its recent conversation context within token limits. Returns the most recent memories for a session, bounded by max_tokens.
No parameter schema on file.
Store or update a vector embedding with metadata. Supports 384, 768, 1024, or 1536 dimensions. Dimension is auto-detected and validated. Use when you have a pre-computed embedding vector to store or update. For embedding text and storing in one step, use zerodb_embed_and_store instead.
No parameter schema on file.
Batch upsert multiple vectors for efficiency. Use when storing many vectors at once to reduce API round-trips. Accepts an array of vector objects and processes them in a single request.
No parameter schema on file.
Search vectors using semantic similarity. Supports 384, 768, 1024, or 1536 dimension query vectors. Auto-detects dimension. Use when searching raw vector embeddings by similarity with a query vector. Unlike zerodb_semantic_search which accepts text (auto-embeds), this requires a pre-computed…
No parameter schema on file.
Delete a specific vector by ID. Use when removing a single vector embedding from the store. WARNING: This operation is irreversible.
No parameter schema on file.
Retrieve a specific vector by ID. Use when you need to inspect a particular vector's metadata or embedding values. Optionally includes the full embedding array.
No parameter schema on file.
List vectors in a project/namespace with pagination. Use when the agent needs to browse or enumerate stored vectors, or answer "what vectors exist?". Supports filtering by namespace and metadata.
No parameter schema on file.
Get vector statistics for a project. Use when checking how many vectors are stored, their dimensions, and namespace distribution. Returns counts, dimension breakdowns, and optionally detailed statistics.
No parameter schema on file.
Create optimized index for vector search. Use when search performance needs improvement on large vector collections. Supports IVF, HNSW, and flat index types with configurable distance metrics.
No parameter schema on file.
Optimize vector storage for better performance. Use when vector search is slow or storage needs compaction. Supports compress, reindex, and deduplicate operations. Use dry_run to preview changes first.
No parameter schema on file.
Export vectors to various formats (JSON, CSV, Parquet). Use when you need to download or migrate vector data out of ZeroDB. Supports filtering by namespace and metadata.
No parameter schema on file.
Compress vector using TurboQuant (PolarQuant + QJL) algorithm from Google Research (ICLR 2026). Achieves ~3.5x compression with 0.9999+ cosine similarity preservation. Data-oblivious — no calibration needed. Returns base64-encoded compressed data.
No parameter schema on file.
Decompress a TurboQuant-compressed vector back to original dimensions. Reconstructs the full vector from the base64-encoded compressed data returned by zerodb_quantum_compress.
No parameter schema on file.
Hybrid similarity search combining cosine similarity with metadata boosting. Returns ranked results with configurable weighting between similarity score and metadata relevance.
No parameter schema on file.
Analyze vector space characteristics for optimal TurboQuant compression settings. Reports sparsity, magnitude distribution, and recommended precision level.
No parameter schema on file.
Transform vector into feature space for enhanced similarity computation. Applies configurable feature mapping for dimensionality transformation.
No parameter schema on file.
Calculate kernel similarity between two vectors. Supports fidelity (normalized dot product squared) and swap_test kernel types for measuring vector similarity.
No parameter schema on file.
Create a new NoSQL table with schema. Use when you need to set up a new data structure for storing structured records. Define fields and indexes for the table schema.
No parameter schema on file.
List all NoSQL tables in the project with their schemas. Use when the agent needs to discover available data structures or answer "what tables exist?". Returns table names, row counts, and field definitions.
No parameter schema on file.
Get table details and schema. Use when you need to inspect a specific table's structure, field types, indexes, and optionally row count statistics.
No parameter schema on file.
Delete a table and all its data. Use when a table is no longer needed and should be permanently removed. Requires confirm flag. WARNING: This operation is irreversible.
No parameter schema on file.
Insert rows into a table. Use when adding new records to a NoSQL table. Accepts an array of row objects and optionally returns inserted IDs.
No parameter schema on file.
Query rows from a table with filters. Use when reading data from a NoSQL table. Supports MongoDB-style filters, sorting, pagination, and field projection.
No parameter schema on file.
Update rows in a table. Use when modifying existing records in a NoSQL table. Supports MongoDB-style update operators ($set, $inc, etc.) and optional upsert behavior.
No parameter schema on file.
Delete rows from a table matching a filter. Use when removing specific records from a NoSQL table. Supports MongoDB-style filters. WARNING: This operation is irreversible.
No parameter schema on file.
Upload file to ZeroDB storage. Use when you need to store a file (base64-encoded) in the project's S3-compatible object storage. Supports metadata and virtual folder organization.
No parameter schema on file.
Download file from ZeroDB storage. Use when you need to retrieve a previously uploaded file by its ID. Returns base64-encoded content by default.
No parameter schema on file.
List files in project storage. Use when the agent needs to discover available files or answer "what files are stored?". Supports filtering by folder and MIME type with pagination.
No parameter schema on file.
Delete file from storage. Use when a file is no longer needed and should be permanently removed. WARNING: This operation is irreversible.
No parameter schema on file.
Get file metadata without downloading content. Use when you need to check a file's size, type, upload date, or custom metadata without fetching the actual file data.
No parameter schema on file.
Generate presigned URL for file access. Use when you need a temporary URL to share file access with external systems. Supports download and upload operations with configurable expiration.
No parameter schema on file.
Create an event in the event stream. Use when you need to publish an event for tracking, auditing, or triggering downstream workflows. Supports event types, payloads, and correlation IDs.
No parameter schema on file.
List events with filtering. Use when you need to browse or query the event stream by type, source, or time range. Supports pagination for large result sets.
No parameter schema on file.
Get event details by ID. Use when you need to inspect a specific event's full payload, timestamps, and metadata.
No parameter schema on file.
Subscribe to event stream (returns subscription ID). Use when you need to set up real-time event notifications. Supports filtering by event type and optional webhook delivery.
No parameter schema on file.
Get event stream statistics. Use when you need to understand event volume, frequency, and distribution over time. Supports filtering by event type and time range.
No parameter schema on file.
Create a new ZeroDB project. Use when you need to set up a new isolated workspace for storing vectors, tables, files, and events. Projects are the top-level organizational unit.
No parameter schema on file.
Get project details. Use when you need to inspect a project's configuration, settings, and enabled features. Uses the configured project ID by default.
No parameter schema on file.
List all accessible projects. Use when the agent needs to discover available projects or answer "what projects do I have access to?". Returns project names, IDs, and basic info.
No parameter schema on file.
Update project settings. Use when you need to modify a project's name, description, or configuration settings.
No parameter schema on file.
Delete a project and all its data. Use when a project is no longer needed. Removes all vectors, tables, files, and events within the project. Requires confirm flag. WARNING: This operation is irreversible.
No parameter schema on file.
Get project usage statistics. Use when you need to check storage consumption, vector counts, API call volumes, and other usage metrics for a project.
No parameter schema on file.
Enable database features for a project. Use when you need to activate specific capabilities (vectors, compression, nosql, files, events) on a project that does not yet have them enabled.
No parameter schema on file.
Collect user interaction for RLHF training. Use when recording a prompt-response pair with optional feedback score for reinforcement learning. Each call creates a new training data point.
No parameter schema on file.
Collect agent-level feedback. Use when recording user satisfaction signals (thumbs up/down, ratings) for a specific agent. Useful for tracking agent quality over time.
No parameter schema on file.
Collect workflow-level feedback. Use when recording the outcome of a multi-step workflow including success status, duration, and steps completed.
No parameter schema on file.
Collect error report for RLHF improvement. Use when recording errors encountered during agent operation to improve future behavior. Include sanitized stack traces and severity levels.
No parameter schema on file.
Get RLHF collection status. Use when you need to check whether RLHF data collection is active and how many interactions have been recorded for a session.
No parameter schema on file.
Get RLHF data summary and statistics. Use when you need an overview of collected RLHF data including interaction counts, average feedback scores, and trends over time.
No parameter schema on file.
Start RLHF data collection for session. Use when initiating RLHF tracking at the beginning of an agent session. Safe to call multiple times — idempotent for the same session.
No parameter schema on file.
Stop RLHF data collection for session. Use when ending RLHF tracking at the end of an agent session. Optionally exports collected data before stopping.
No parameter schema on file.
Get RLHF interactions for a session. Use when reviewing all recorded interactions within a specific RLHF session for analysis or export.
No parameter schema on file.
Broadcast RLHF event to subscribers. Use when sending RLHF-related notifications to specific agents or all subscribers. Supports targeted delivery to specific agent IDs.
No parameter schema on file.
Get system-wide statistics (admin only). Use when you need a global view of platform performance and usage metrics. Requires admin privileges.
No parameter schema on file.
List all projects system-wide (admin only). Use when you need to see all projects across all users for administrative purposes. Supports filtering by user ID. Requires admin privileges.
No parameter schema on file.
Get user usage statistics (admin only). Use when you need to inspect a specific user's resource consumption and API usage. Requires admin privileges.
No parameter schema on file.
Get system health status (admin only). Use when you need to check the health of all system components (database, storage, search). Requires admin privileges.
No parameter schema on file.
Run database optimization (admin only). Use when the database needs maintenance such as vacuum, reindex, or analyze operations. Supports dry_run to preview changes. Requires admin privileges.
No parameter schema on file.
Execute SQL query on provisioned PostgreSQL instance with security validations. Use when you need to run arbitrary SQL (SELECT, INSERT, UPDATE, DELETE) against the dedicated PostgreSQL database. Supports parameterized queries and read-only mode enforcement.
No parameter schema on file.
Get database schema information (tables, columns, indexes). Use when you need to discover or inspect the PostgreSQL schema structure. Returns table definitions, column types, indexes, and constraints.
No parameter schema on file.
Create new PostgreSQL table with schema definition. Use when you need to define a new relational table with typed columns, constraints, and indexes. Supports if_not_exists for idempotent creation.
No parameter schema on file.
Trigger PostgreSQL backup job. Use when you need to create a point-in-time backup of the database. Supports full and incremental backups with configurable retention and compression.
No parameter schema on file.
Restore PostgreSQL database from backup. Use when you need to recover data from a previous backup. Supports full, schema-only, and data-only restore types. WARNING: This operation is irreversible — it overwrites existing data when confirm_overwrite is true.
No parameter schema on file.
Get PostgreSQL database statistics (size, connections, query performance). Use when you need to monitor database health, connection pool usage, storage consumption, and query performance metrics.
No parameter schema on file.
Execute a read-only (SELECT/WITH only) SQL query against the project lakehouse via DuckDB over Parquet files in object storage. Use when you need to analyze or inspect data that has been ingested into the lakehouse. Destructive SQL (INSERT/UPDATE/DELETE/DROP/etc.) is rejected.
No parameter schema on file.
List the lakehouse tables (sensor-type partitions) available for a project, with file counts, total bytes, and last-modified time. Use when you need to discover what data exists in the lakehouse before querying it.
No parameter schema on file.
List all partitions in the public lakehouse data catalog, with file counts and sizes. Use when you need a platform-wide overview of available lakehouse data, independent of any single project. No project_id required.
No parameter schema on file.
Search the public lakehouse data catalog by partition name. Use when you need to find which lakehouse partitions match a keyword (e.g. "weather", "ais") before querying them.
No parameter schema on file.
Provision a dedicated PostgreSQL instance via Railway with dedicated resources. Use when you need to spin up a new managed PostgreSQL database. Choose instance size based on workload requirements and budget.
No parameter schema on file.
Get status and health metrics for dedicated PostgreSQL instance. Use when you need to check if your PostgreSQL instance is running, its uptime, and health indicators.
No parameter schema on file.
Get connection credentials for PostgreSQL instance (database_url, host, port, etc.). Use when you need connection details to configure applications or tools. Supports primary, readonly, and admin credential types.
No parameter schema on file.
Get usage statistics and billing information for PostgreSQL instance. Use when you need to review compute usage, storage consumption, and cost breakdown for your dedicated instance.
No parameter schema on file.
Get SQL query logs with performance metrics and credit consumption. Use when you need to audit queries, debug slow operations, or review credit usage. Supports filtering by query type.
No parameter schema on file.
Restart the dedicated PostgreSQL instance (completes in 30-60 seconds). Use when the instance needs a restart due to configuration changes or performance issues. Does not lose data.
No parameter schema on file.
Delete the PostgreSQL instance and all data (requires confirmation). Use when the instance is no longer needed. Requires confirm=true. WARNING: This operation is irreversible.
No parameter schema on file.
Create or update a knowledge graph entity. Use when you need to add a person, organization, technology, or concept to the context graph, or refresh an existing one. If the entity already exists (matched by canonical_name + entity_type), aliases are merged and memory_count is incremented rather…
No parameter schema on file.
Create or strengthen a directed edge (relationship) between two existing entities in the knowledge graph. Use when you have identified a relationship between two entities you have already created with zerodb_graph_upsert_entity. Both entities must already exist — this does not create them. Unlike…
No parameter schema on file.
Multi-hop traversal of the knowledge graph starting from an entity. Use when you need to discover what is connected to an entity, directly or transitively, up to a bounded depth. Returns nodes, edges, and paths discovered within max_hops. Unlike zerodb_graph_rag_search which ranks results by…
No parameter schema on file.
GraphRAG hybrid search — blends vector similarity with knowledge graph proximity. Use when you want search results that are both semantically relevant to a query AND structurally connected in the entity graph, rather than relying on vector similarity alone. graph_weight=0.0 behaves like pure…
No parameter schema on file.
Manually renew authentication token. Use when the current auth token has expired or is about to expire and you need to force a refresh before the next API call.
No parameter schema on file.
Free
$0 forever
- Every tool, no call limit
- No card, and mcprush charges nothing for it
- Source published under MIT
- Runs on your machine — nothing of it reaches our gateway
- 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 Ainative Zerodb 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: —
ATrust score 93 / 100
Release 2.4.1 · scanned 13 Oct 2026
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.
Threat score100
Client score93
Findings0 threat · 4 capability
Capabilityhigh
Coveragesource
Verificationrepo
Surface digestc099301e5b0bb75ebc2dbc0673d71303ab3dbeeef6311e78401af7496419495a
Score vectorthreat 100 → client 93
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | high | capability blast radius (high) — client exposure if the model is manipulated | −6 |
| verification-discount | repo | publisher verification (public source) — no provenance, but the source is public and inspectable | −1 |
| coverage-honesty | source | inspection depth (source) — how much of the target the scan could see | −0 |
score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
Tool surfaceread
Implementation sourceread
Package metadataread
Live transportnot available
Tools were statically extracted from the published source (85 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. high is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| zerodb_generate_embeddings | state-write | state-write: declares readOnlyHint: false |
| zerodb_embed_and_store | state-write | state-write: declares readOnlyHint: false |
| zerodb_semantic_search | no tags | |
| zerodb_store_memory | state-write | state-write: declares readOnlyHint: false |
| zerodb_search_memory | no tags | |
| zerodb_get_context | no tags | |
| zerodb_upsert_vector | state-write | state-write: declares readOnlyHint: false |
| zerodb_batch_upsert_vectors | state-write | state-write: declares readOnlyHint: false |
| zerodb_search_vectors | no tags | |
| zerodb_delete_vector | state-write | state-write: declares readOnlyHint: false, destructiveHint: true |
| zerodb_get_vector | no tags | |
| zerodb_list_vectors | untrusted-input | untrusted-input: keyword "browse" |
| zerodb_vector_stats | no tags | |
| zerodb_create_vector_index | state-write | state-write: declares readOnlyHint: false |
| zerodb_optimize_vectors | state-write | state-write: declares readOnlyHint: false |
| zerodb_export_vectors | untrusted-input | untrusted-input: keyword "download" |
| zerodb_quantum_compress | state-write | state-write: declares readOnlyHint: false |
| zerodb_quantum_decompress | state-write | state-write: declares readOnlyHint: false |
| zerodb_quantum_hybrid_search | no tags | |
| zerodb_quantum_optimize | state-write | state-write: declares readOnlyHint: false |
| zerodb_quantum_feature_map | state-write | state-write: declares readOnlyHint: false |
| zerodb_quantum_kernel | no tags | |
| zerodb_create_table | state-write | state-write: declares readOnlyHint: false |
| zerodb_list_tables | no tags | |
| zerodb_get_table | no tags | |
| zerodb_delete_table | state-write | state-write: declares readOnlyHint: false, destructiveHint: true |
| zerodb_insert_rows | state-write | state-write: declares readOnlyHint: false |
| zerodb_query_rows | no tags | |
| zerodb_update_rows | state-write | state-write: declares readOnlyHint: false |
| zerodb_delete_rows | state-write | state-write: declares readOnlyHint: false, destructiveHint: true |
| zerodb_upload_file | external-sinkstate-write | external-sink: keyword "upload_file"; state-write: declares readOnlyHint: false |
| zerodb_download_file | untrusted-input | untrusted-input: keyword "download" |
| zerodb_list_files | sensitive-source | sensitive-source: keyword "list_files" |
| zerodb_delete_file | file-writestate-write | file-write: keyword "delete_file" in tool name; state-write: declares readOnlyHint: false, destructiveHint: true |
| zerodb_get_file_metadata | no tags | |
| zerodb_generate_presigned_url | untrusted-input | untrusted-input: keyword "download" |
| zerodb_create_event | state-write | state-write: declares readOnlyHint: false |
| zerodb_list_events | untrusted-input | untrusted-input: keyword "browse" |
| zerodb_get_event | no tags | |
| zerodb_subscribe_events | external-sinkstate-write | external-sink: keyword "webhook", parameter "webhook"; state-write: declares readOnlyHint: false |
| zerodb_event_stats | no tags | |
| zerodb_create_project | state-write | state-write: declares readOnlyHint: false |
| zerodb_get_project | no tags | |
| zerodb_list_projects | no tags | |
| zerodb_update_project | state-write | state-write: declares readOnlyHint: false |
| zerodb_delete_project | state-write | state-write: declares readOnlyHint: false, destructiveHint: true |
| zerodb_get_project_stats | no tags | |
| zerodb_enable_database | state-write | state-write: declares readOnlyHint: false |
| zerodb_rlhf_interaction | state-write | state-write: declares readOnlyHint: false |
| zerodb_rlhf_agent_feedback | state-write | state-write: declares readOnlyHint: false |
| zerodb_rlhf_workflow | state-write | state-write: declares readOnlyHint: false |
| zerodb_rlhf_error | state-write | state-write: declares readOnlyHint: false |
| zerodb_rlhf_status | no tags | |
| zerodb_rlhf_summary | no tags | |
| zerodb_rlhf_start | state-write | state-write: declares readOnlyHint: false |
| zerodb_rlhf_stop | state-write | state-write: declares readOnlyHint: false |
| zerodb_rlhf_session | no tags | |
| zerodb_rlhf_broadcast | state-write | state-write: declares readOnlyHint: false |
| zerodb_admin_system_stats | no tags | |
| zerodb_admin_list_projects | no tags | |
| zerodb_admin_user_usage | no tags | |
| zerodb_admin_health | no tags | |
| zerodb_admin_optimize | state-write | state-write: declares readOnlyHint: false |
| zerodb_postgres_query | sensitive-sourcestate-write | sensitive-source: keyword "execute_sql", parameter "sql"; state-write: declares readOnlyHint: false |
| zerodb_postgres_schema_info | no tags | |
| zerodb_postgres_create_table | state-write | state-write: declares readOnlyHint: false |
| zerodb_postgres_backup | state-write | state-write: declares readOnlyHint: false |
| zerodb_postgres_restore | state-write | state-write: declares readOnlyHint: false, destructiveHint: true |
| zerodb_postgres_stats | no tags | |
| zerodb_lakehouse_query | sensitive-source | sensitive-source: keyword "sql_query", parameter "sql" |
| zerodb_lakehouse_list_tables | no tags | |
| zerodb_lakehouse_catalog_list | no tags | |
| zerodb_lakehouse_catalog_search | no tags | |
| zerodb_provision_postgres | state-write | state-write: declares readOnlyHint: false |
| zerodb_get_postgres_status | no tags | |
| zerodb_get_postgres_connection | no tags | |
| zerodb_get_postgres_usage | no tags | |
| zerodb_get_postgres_logs | sensitive-source | sensitive-source: keyword "sql_query" |
| zerodb_restart_postgres | state-write | state-write: declares readOnlyHint: false |
| zerodb_delete_postgres | state-write | state-write: declares readOnlyHint: false, destructiveHint: true |
| zerodb_graph_upsert_entity | state-write | state-write: declares readOnlyHint: false |
| zerodb_graph_create_edge | state-write | state-write: declares readOnlyHint: false |
| zerodb_graph_traverse | no tags | |
| zerodb_graph_rag_search | no tags | |
| zerodb_renew_token | state-write | state-write: declares readOnlyHint: false |
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
zerodb_download_file → zerodb_get_postgres_logs → zerodb_subscribe_events
A cross-tool exfiltration chain exists: zerodb_download_file → zerodb_get_postgres_logs → zerodb_subscribe_events.
Supply chain and provenance
Integrityfirst-seen
Surface digestc099301e5b0bb75e
Scanned2026-10-13
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
Always latest — the install command names no version, so it installs the newest release when it runs; the current release on file is 2.4.1. Pin a release below and the command asks for exactly that one.
2.4.1
4 Oct 2026
latestNo release note was published with this version.
2.3.5
25 Sep 2026
No release note was published with this version.
2.3.2
undated
- The version this listing was on when mcprush began following its releases. The registry was not asked when it shipped, so this row carries no date.
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