Search, save and rate AI tools people shared in chats. Local catalogue, any model or none.
Nothing to run from here
Agent Data Tools: AI 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
tool-list score
15
tools declared
remote
at its publisher
—
calls last 7d
What it does
25 tools: LLM chat, summaries, translation, embeddings, speech, images. 25 free calls.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http agent-data-tools-ai-mcp https://agent-data-tools.revmesh2074.workers.dev/mcp/ai
# 2 — ask your agent for something these tools do
# image, transcribe, describe and 12 more
Agent Data Tools: AI costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
NUAll 8 servers
Nutshell20008 servers
7 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. 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 agent-data-tools-ai-mcp https://agent-data-tools.revmesh2074.workers.dev/mcp/aiReconnect, 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 asks of you
Nothing is required, but it can take Authorization header (Optional. 'Bearer adt_...' API key from https://agent-data-tools.revmesh2074.workers.dev/credits to pay by card. Leave empty to pay each call with x402 (USDC).) if you want to set it.
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
15 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.
Text-to-image generation with FLUX.1 schnell. Send a prompt, get a 1024x1024 JPEG back as base64 in a few seconds. Use for illustrations, thumbnails, mockups, avatars and social media images. Optional steps parameter (1-8, default 4) trades speed for detail. Example: prompt=a lighthouse on a cliff at sunset, watercolor. Price $0.02/call via x402 USDC or a card key (/credits); failed calls free. Re
| Parameter | Type | Required | Notes |
|---|---|---|---|
| prompt | string | yes | What the image should show (3-800 characters) |
| steps | integer | no | Diffusion steps, 1-8 (default 4) |
Transcribe speech from an audio file at a public URL using Whisper large-v3-turbo. Returns the transcript text, detected language, duration and word count. Accepts common formats such as MP3, WAV, M4A and OGG up to 5 MB. Use for voice notes, podcast clips, meeting snippets and voice messages. Example: url=https://commons.wikimedia.org/wiki/Special:FilePath/En-us-hello.ogg. Price $0.02/call via x40
| Parameter | Type | Required | Notes |
|---|---|---|---|
| url | string | yes | Absolute http(s) URL of an audio file (max 5 MB) |
Vision model for an image at a public URL: get a detailed description including any visible text, or pass a question to ask something specific about the image. Accepts PNG, JPEG, WebP and GIF up to 3 MB. Use for alt text, OCR-style reading of screenshots, chart reading and content checks. Price $0.01/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes
| Parameter | Type | Required | Notes |
|---|---|---|---|
| url | string | yes | Absolute http(s) URL of a PNG, JPEG, WebP or GIF image (max 3 MB) |
| question | string | no | Optional question about the image (max 300 characters); default is a detailed description |
Send a prompt, get an answer from Llama 3.1 8B Instruct, with an optional system prompt, up to 1,024 output tokens and adjustable temperature. Use for drafting, reasoning steps, Q&A and any quick LLM call without an AI provider account. Example: prompt=Explain x402 in one sentence.. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes noth
| Parameter | Type | Required | Notes |
|---|---|---|---|
| prompt | string | yes | User prompt, up to 8,000 characters |
| system | string | no | Optional system prompt, up to 2,000 characters |
| maxTokens | integer | no | Maximum output tokens, 1-1024 (default 400) |
| temperature | number | no | 0-1.5 (default 0.6) |
Send a prompt, get an answer from a larger open model: Llama 3.3 70B Instruct (default) or OpenAI gpt-oss-120b, with an optional system prompt, up to 1,024 output tokens and adjustable temperature. Same call as /ai/chat with a stronger model. Use when the 8B model is not enough: reasoning, drafting and Q&A. Example: prompt=Explain x402 in one sentence.. Price $0.01/call via x402 USDC or a card key
| Parameter | Type | Required | Notes |
|---|---|---|---|
| prompt | string | yes | User prompt, up to 8,000 characters |
| model | string | no | llama-3.3-70b (default) or gpt-oss-120b |
| system | string | no | Optional system prompt, up to 2,000 characters |
| maxTokens | integer | no | Maximum output tokens, 1-1024 (default 400) |
| temperature | number | no | 0-1.5 (default 0.6) |
Summarize up to 12,000 characters of text you send into a few sentences plus bullet key points. Use for long emails, documents, transcripts and tool outputs (for a web page by URL, use /summarize). Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text to summarize, up to 12,000 characters |
| sentences | integer | no | Summary length in sentences, 1-8 (default 3) |
Positive or negative sentiment of English text with a confidence score, from a DistilBERT model fine-tuned on SST-2. Use to triage reviews, support messages, social posts and replies. Example: text=The checkout was fast and support answered within minutes.. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged,
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | English text, up to 4,000 characters |
Zero-shot classification: give text and 2-20 candidate labels, get the best label, a short reason and a ranking. Use for routing tickets, tagging content, intent detection and moderation queues. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text to classify, up to 8,000 characters |
| labels | string | yes | Comma-separated candidate labels (2-20) |
The most important keywords and key phrases of a text, most relevant first. Use for tagging, SEO, search indexing and topic detection. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text, up to 12,000 characters |
| count | integer | no | How many, 3-30 (default 10) |
Rewrite text to be more formal, casual, simpler, shorter, friendlier, more professional or more persuasive, keeping the meaning and language. Use to polish emails, replies, product copy and messages. Example: text=hey, cant make it tmrw, can we move to thu?. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text, up to 8,000 characters |
| style | string | no | formal, casual, simpler, shorter, friendly, professional or persuasive (default professional) |
A structured Markdown outline (headings and bullet points) of a text you send, or a suggested outline for a topic. Use to plan articles, reports, talks and documentation. Example: text=How small businesses can accept stablecoin payments. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text to outline, or a topic, up to 12,000 characters |
| depth | integer | no | Heading levels, 1-3 (default 2) |
Translate text between about 100 languages with Meta's M2M100 1.2B model. Give the target language as an ISO code such as en, sv, de, fr, es, zh or ja; the source language is optional. Use to localise messages and documents. Example: text=Payment received, thank you!, to=sv. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; eac
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text, up to 4,000 characters |
| to | string | yes | Target language code, e.g. sv |
| from | string | no | Source language code (default en) |
A 1,024-dimension embedding vector for up to 4,000 characters of text in 100+ languages, from BAAI's BGE-M3. Use for semantic search, RAG retrieval, clustering and deduplication. Example: text=pay-per-call APIs for AI agents. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text to embed, up to 4,000 characters |
Pull named fields out of unstructured text (emails, invoices, listings, bios) and get them back as a JSON object, with null for anything not present. Use to turn messy text into structured data for an agent. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Source text, up to 12,000 characters |
| fields | string | yes | Comma-separated field names to extract (1-30) |
Turn up to 1,000 characters of text into natural speech as an audio file (base64, with its content type), in English, Spanish, French, Chinese, Japanese or Korean, with MeloTTS. Use for voice replies, audio notes, accessibility and phone or chat bots. Example: text=Your payment was received. Thank you!. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes
| Parameter | Type | Required | Notes |
|---|---|---|---|
| text | string | yes | Text to speak, up to 1,000 characters |
| lang | string | no | Language: en, es, fr, zh, ja or ko (default en) |
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 Agent Data Tools: AI 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: —
ATool-list grade · score 93 / 100
Release 1.82.18 · scanned 28 Oct 2026
Graded from the tools this server lists, not from its source code.
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 · 3 capability
Capabilitymoderate
Coveragemanifest
Verificationnot in this report
Surface digestd032a176160e1802e52dda52b669af27688489ec35b631880b4da09d1bfa1de3
Score vectorthreat 100 → client 93
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | moderate | capability blast radius (moderate) — client exposure if the model is manipulated | −3 |
| coverage-honesty | manifest | inspection depth (manifest) — how much of the target the scan could see | −4 |
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.
The scan read each tool’s name, description, input schema and annotations exactly as the server listed them the last time it answered us; no code was reviewed. We ask the server again about once a month, and a list that changed is graded again.
Tool surfaceread
Implementation sourcenot available
Package metadatanot available
Live transportnot available
The implementation source was not read — this reflects the declared tool metadata only.
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. moderate is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| image | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| transcribe | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| describe | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_chat | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_chat_large | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_summarize_text | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_sentiment | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_classify | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_keywords | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_rewrite | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_outline | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_translate | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_embed | external-sinkuntrusted-input | external-sink: keyword "call_api"; untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_extract_json | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
| ai_speech | untrusted-input | untrusted-input: declares openWorldHint: true (interacts with entities outside the server) |
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.
flow-1
Untrusted input can drive an external action even though no sensitive source is exposed.
Supply chain and provenance
Integrityfirst-seen
Surface digestd032a176160e1802
Scanned2026-10-28
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
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 1.82.18.
1.82.18
undated
latestNo release note was published with this version.
—
no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Agent Data Tools: AI can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.