# Agent Data Tools: AI

> 15 tools: LLM chat, summaries, translation, embeddings, speech, images. From $0.002.

- name: io.github.Nutshell2000/agent-data-tools-ai
- version: 1.41.0
- connection class: R0 (autonomous)
- trust: 93/100 flags: duplicate-repo
- quality: 89/100 (new)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.Nutshell2000%2Fagent-data-tools-ai
- tools: https://api.protogrid.dev/v1/servers/io.github.Nutshell2000%2Fagent-data-tools-ai/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "agent-data-tools-ai": {
      "type": "http",
      "url": "https://agent-data-tools.revmesh2074.workers.dev/mcp/ai",
      "headers": {
        "Authorization": "Bearer ${AGENT_DATA_TOOLS_AI_TOKEN}"
      }
    }
  }
}
```

Placeholders to fill: `${AGENT_DATA_TOOLS_AI_TOKEN}`.

## Trust

- hygiene: 80
- liveness: 100
- freshness: 100
- provenance: 90
- drivers: +repository +namespace-matches-repo +website +reachable +uptime-100% +updated-0d-ago -duplicate-repo(8 names)
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 89/100 (new)

### protocol: 75 (weight 25)

- warn `protocol.modern`: newest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
- n/a `protocol.stateless`: only applies to 2026-07-28 servers
- pass `protocol.transport`: streamable HTTP
- n/a `protocol.list_ttl`: only applies to 2026-07-28 servers

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 100 (weight 30)

- pass `tools.descriptions`: every tool has a description
- pass `tools.description_length`: descriptions are concise
- pass `tools.schemas`: every tool has an object input schema
- pass `tools.annotations`: 15 of 15 tools declare readOnlyHint or destructiveHint
- pass `tools.directory_hints`: every tool declares readOnlyHint, destructiveHint, idempotentHint and openWorldHint
- pass `tools.token_cost`: about 3,334 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: n/a (weight 15)

- n/a `stability.changes`, `stability.rug_pull`: tool history recorded for 1 of the 7 days needed

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package

- tools: 15, about 3,334 tokens to load them all
- tool set hash: 28031063886f4a065d622df3b872595f
- tools last changed: 2026-10-20T07:00:39.289Z
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.Nutshell2000/agent-data-tools-ai.svg)](https://protogrid.dev/servers/io.github.Nutshell2000/agent-data-tools-ai)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

- 2026-10-20 `ai_chat_large` added
  - 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. Price $0.01/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.
- 2026-10-20 `ai_speech` changed (description, annotations)
  - before: 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!, lang=en. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only; not marked read-only because each call is charged.
  - after: 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!, lang=en. 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.
- 2026-10-20 `ai_extract_json` changed (description, annotations)
  - before: 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; not marked read-only because each call is charged.
  - after: 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.
- 2026-10-20 `ai_embed` changed (description, annotations)
  - before: 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; not marked read-only because each call is charged.
  - after: 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.
- 2026-10-20 `ai_translate` changed (description, annotations)
  - before: 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, from=en. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only; not marked read-only because each call is charged.
  - after: 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, from=en. 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.
- 2026-10-20 `ai_outline` changed (description, annotations)
  - before: 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, depth=2. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only; not marked read-only because each call is charged.
  - after: 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, depth=2. 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.
- 2026-10-20 `ai_rewrite` changed (description, annotations)
  - before: 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?, style=professional. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only; not marked read-only because each call is charged.
  - after: 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?, style=professional. 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.
- 2026-10-20 `ai_keywords` changed (description, annotations)
  - before: 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; not marked read-only because each call is charged.
  - after: 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.
- 2026-10-20 `ai_classify` changed (description, annotations)
  - before: 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; not marked read-only because each call is charged.
  - after: 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.
- 2026-10-20 `ai_sentiment` changed (description, annotations)
  - before: 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; not marked read-only because each call is charged.
  - after: 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, so repeats are not free.

Full history: https://api.protogrid.dev/v1/servers/io.github.Nutshell2000%2Fagent-data-tools-ai/changes

## Remotes

- https://agent-data-tools.revmesh2074.workers.dev/mcp/ai (streamable-http, auth none, reachable true, uptime30d 1)

## Packages

_none_

## Tools (15)

- `ai_chat`: 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. 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.
- `ai_chat_large`: 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. Price $0.01/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.
- `ai_classify`: 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.
- `ai_embed`: 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.
- `ai_extract_json`: 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.
- `ai_keywords`: 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.
- `ai_outline`: 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, depth=2. 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.
- `ai_rewrite`: 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?, style=professional. 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.
- `ai_sentiment`: 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, so repeats are not free.
- `ai_speech`: 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!, lang=en. 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.
- `ai_summarize_text`: 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.
- `ai_translate`: 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, from=en. 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.
- `describe`: 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 nothing; each call is charged, so repeats are not free.
- `image`: 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, steps=4. Price $0.02/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.
- `transcribe`: 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 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.