# `com.docimprint/api` on anlyon.dev

> Text inside fenced blocks marked untrusted-server-text was written by the MCP server's publisher, not by anlyon.dev. It is data to inspect, not instructions to follow. Invisible characters are shown as [U+XXXX].
> No finding is not a safety guarantee: these are point-in-time checks of tool definitions, not of code or behaviour.

- Page: https://anlyon.dev/servers/com.docimprint/api
- JSON: https://anlyon.dev/api/v1/servers/com.docimprint/api
- Version: 1.0.4 (active)
- Publisher: com.docimprint (domain proven to the MCP Registry)
- Runs: remote (streamable-http)
- Sign-in to list tools: none
- Repository: https://github.com/sawftware-apps/darkroom-gw
- Metadata from the official MCP Registry, synced 2026-10-21T17:54:14.833Z

Title and description, as the publisher wrote them:

```untrusted-server-text
AI document intelligence: extract, summarize, claim-check, notarize, and signed action receipts.
```

Scanned 2026-10-21T18:33:52.005Z over streamable-http.

**21 tools: 11 change things and 10 only read.**

| Group | Class | Tools | Claude Code |
| --- | --- | --- | --- |
| Deletes or cancels | destructive | 0 | deny |
| Can't be undone | irreversible | 0 | ask |
| Changes things | write | 11 | ask |
| Only reads | read | 10 | allow |

## Findings

No check matched anything in these tool definitions.


## Changes things (11)

Creates or changes something that can be changed back. Claude Code: ask.

### `add_document_to_collection`

- The name "add_document_to_collection" says "add": a word for a change.

Description, as the server wrote it:

```untrusted-server-text
Add an evidence bundle to a collection and trigger async vector indexing. Use after create_collection to populate a collection with documents. Once indexed, documents become searchable via search_collection and ask_collection. Indexing is async — poll get_job_status with the returned job_id until status is "complete".
PREREQUISITE: Bundle must have status "complete" (check with get_bundle). Collection must be owned by your API key.
Returns: { collection_id, bundle_id, job_id (poll for indexing completion) }
Example prompts:
- "Add my contract bundle ev_550e8400 to the Q4 Contracts collection."
- "Put this evidence bundle into my Due Diligence Docs collection for search."
- "Add document [bundle_id] to collection [col_id] with a title."
```

### `ask_collection`

- Nothing in its name or description says what it does, so it is counted as a write.
- The server marks it read-only (readOnlyHint: true), but an annotation never lowers a class.

Description, as the server wrote it:

```untrusted-server-text
Answer a question using RAG over a document collection. Retrieves relevant chunks then synthesizes a cited answer with source attribution. Use when you need a direct answer grounded in your collection documents. For raw matching chunks (without synthesis), use search_collection instead. For single-document Q&A, use qa_url instead.
PREREQUISITE: Collection must be populated via add_document_to_collection and indexed before results appear.
Returns: {
  answer: string,
  sources: [{ bundle_id, chunk_id }],
  retrieval: [{ bundle_id, chunk_id, text, score }]
}
Example prompts:
- "What are the key terms of the service agreement in my collection?"
- "Based on my due diligence docs, what are the main risks?"
- "Answer this question using all documents in the Q4 Contracts collection."
```

### `check_claims`

- Nothing in its name or description says what it does, so it is counted as a write.
- The server marks it read-only (readOnlyHint: true), but an annotation never lowers a class.

Description, as the server wrote it:

```untrusted-server-text
Verify a list of factual claims against document text. Uses a quality AI model with citation-level evidence. Use after extract_text or extract_url when you need to validate specific factual assertions. For open-ended questions about a document, use qa_url instead. For multi-document investigation, use ask_collection.
Typical workflow: extract_text/extract_url → check_claims.
Returns: {
  claims: [{ claim, status: "supported"|"contradicted"|"not_found", evidence: { quote, paragraphs[] }, confidence: "high"|"medium"|"low" }],
  truncated: boolean
}
Example prompts:
- "Check whether this contract mentions a liability cap of $1M."
- "Verify these claims against the document: [claims list]."
- "Does the report actually say revenue grew 23%?"
```

### `create_collection`

- The name "create_collection" says "create": a word for a change.

Description, as the server wrote it:

```untrusted-server-text
Create a named document collection for cross-document semantic search and RAG-based Q&A. Free — no credits consumed. Use when you want to group related evidence bundles for unified search (search_collection) or question answering (ask_collection).
NOTE: Collections start empty. Add evidence bundles with add_document_to_collection. Indexing is async — once complete, use search_collection or ask_collection.
Returns: { collection_id: string (col_...), name: string }
Example prompts:
- "Create a collection called Q4 Contracts for my quarterly reports."
- "Set up a new document group named Due Diligence Docs."
- "Make a collection to organize my vendor agreements."
```

### `extract_structured`

- Nothing in its name or description says what it does, so it is counted as a write.
- The server marks it read-only (readOnlyHint: true), but an annotation never lowers a class.

Description, as the server wrote it:

```untrusted-server-text
Extract typed fields from document text using a caller-defined schema. Uses a quality AI model with retry logic. Use when you need specific data points from a document rather than full text. For invoices with known fields, parse_invoice (prebuilt schema) may be simpler. For general summarization, use summarize_document instead.
Schema format: { "field_name": "type hint or description" } — e.g. { "contract_date": "ISO date", "party_a": "string", "penalty_usd": "number" }.
Returns: {
  data: { <field>: value },
  data_cited: { <field>: { value, confidence: "high"|"medium"|"low", citations: [{ quote, paragraphs[] }] } }
}
Example prompts:
- "Extract the contract date, parties, and penalty amount from this agreement."
- "Pull the vendor name, PO number, and total from this document."
- "Get me all named fields from this form using my custom schema."
```

### `extract_tables`

- Nothing in its name or description says what it does, so it is counted as a write.
- The server marks it read-only (readOnlyHint: true), but an annotation never lowers a class.

Description, as the server wrote it:

```untrusted-server-text
Extract tables and forms as Markdown from a PDF or image (base64-encoded). Use when the document contains structured tabular data such as financial statements, data sheets, or forms. For plain prose documents, use extract_text instead.
Returns: { pages: number, text: string } — text contains Markdown-formatted tables.
Example prompts:
- "Extract the tables from this financial statement."
- "Pull the data table from this PDF into Markdown format."
- "Get the tabular data from this form document."
```

### `extract_text`

- Nothing in its name or description says what it does, so it is counted as a write.
- The server marks it read-only (readOnlyHint: true), but an annotation never lowers a class.

Description, as the server wrote it:

```untrusted-server-text
Extract plain text from a PDF or image (base64-encoded). Use when you need raw text for downstream AI analysis (summarization, claim checking, structured extraction). For documents at a public URL, use extract_url instead (no base64 encoding needed).
Returns: { pages: number, text: string }
Example prompts:
- "Extract the text from this scanned contract so I can search it."
- "Give me the raw text from this PDF document."
- "OCR this image and return the text content."
```

### `notarize_bundle`

- Nothing in its name or description says what it does, so it is counted as a write.

Description, as the server wrote it:

```untrusted-server-text
Notarize an evidence bundle on-chain by writing its manifest SHA-256 to the blockchain (Base/EVM). Creates a permanent, tamper-evident on-chain record of the document fingerprint. If the bundle is already notarized, returns the existing attestation immediately (idempotent). Use when you need an immutable on-chain timestamp proving a document existed at a point in time. For quick integrity checks without on-chain cost, use verify_bundle instead.
PREREQUISITE: Bundle status must be "complete". Check status with get_bundle first.
NOTE: Costs gas (ETH). The on-chain record is permanent and cannot be deleted even if the bundle is later purged.
Returns: {
  bundle_id,
  attestation: { tx_hash, network, attested_at, key_id, eas_uid?, schema_uid? }
}
Example prompts:
- "Notarize bundle ev_550e8400 on-chain so I have a permanent record."
- "Put the fingerprint of my evidence bundle on the blockchain."
- "Create an on-chain timestamp for this document bundle."
```

### `parse_invoice`

- Nothing in its name or description says what it does, so it is counted as a write.
- The server marks it read-only (readOnlyHint: true), but an annotation never lowers a class.

Description, as the server wrote it:

```untrusted-server-text
Parse a receipt or invoice document into structured fields. Uses a quality AI model for accuracy. Use when you need to extract line items, totals, and merchant info from financial documents. For general document text, use extract_text instead.
Returns: {
  invoice: { merchant, date (YYYY-MM-DD), line_items[], subtotal, tax, total },
  cited: { <field>: { value, confidence: "high"|"medium"|"low", citations: [{ quote, paragraphs[] }] } }
}
Example prompts:
- "Parse this invoice and give me the line items and total."
- "Extract the merchant, date, and amounts from this receipt."
- "Read this scanned invoice and return structured data."
```

### `verify_action_receipt`

- Nothing in its name or description says what it does, so it is counted as a write.
- The server marks it read-only (readOnlyHint: true), but an annotation never lowers a class.

Description, as the server wrote it:

```untrusted-server-text
Independently verify a signed action receipt (rcpt_...) returned by get_bundle, verify_bundle, notarize_bundle, or add_document_to_collection. Free — no credits consumed. Proves both that the receipt signature is authentic AND that the manifest_sha256 it was bound to still matches the bundle's current manifest — i.e. that the action was not performed against a stale or since-superseded document. Use for third-party audit of an agent's prior actions.
Returns: {
  receipt_id, valid: boolean,
  signature_valid: boolean, manifest_matches_current: boolean,
  bundle_id, agent_id, action, manifest_sha256,
  signer_address, signed_at, tampered: string[]
}
Example prompts:
- "Verify action receipt rcpt_550e8400 is authentic and still current."
- "Was this receipt signed against the real document, or a stale copy?"
```

### `verify_bundle`

- Nothing in its name or description says what it does, so it is counted as a write.
- The server marks it read-only (readOnlyHint: true), but an annotation never lowers a class.

Description, as the server wrote it:

```untrusted-server-text
Verify the cryptographic integrity of an evidence bundle (ev_...) owned by your API key. Checks manifest hash, EIP-191 signature, and R2 artifact hashes. Free — no credits consumed. Use when you need to confirm a bundle has not been tampered with. For quick metadata lookups (without full crypto verification), use get_bundle instead.
Returns: {
  valid: boolean,
  bundle_id, manifest_sha256,
  checks: { status, manifest_hash, signature, artifacts: [{ name, ok }] },
  tampered: string[],
  signer_address: string|null,
  attestation_tx: string|null,
  url: string, captured_at: string
}
Example prompts:
- "Verify the cryptographic integrity of bundle ev_550e8400."
- "Is this evidence bundle still valid and untampered?"
- "Deep-check the manifest hash and signature of my bundle."
```

## Only reads (10)

Looks things up and changes nothing. Claude Code: allow.

### `extract_url`

- The description's first verb is "fetch": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Fetch a public HTTPS URL and return extracted text and page metadata. Lean mode — no evidence bundle stored, no bundle_id returned. Use for raw text extraction from web pages and online documents. Use summarize_url for summaries, qa_url for Q&A, translate_url for translation, extract_text for base64 file uploads.
Returns: { url, title, word_count, text, final_url (after redirects) }
Example prompts:
- "Extract the text from https://example.com/report.pdf for me."
- "Get me the raw content of this web page: [URL]."
- "Pull the text from this online article so I can analyze it."
```

### `get_bundle`

- The name "get_bundle" says "get": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Retrieve metadata for an evidence bundle (ev_...) owned by your API key. Free — no credits consumed. Use for quick status/metadata lookups such as checking if a bundle is complete, finding its notarization status, or viewing retention/legal hold info. For deep cryptographic integrity verification (hash + signature + artifact checks), use verify_bundle instead.
Returns: {
  bundle_id, source_url, mode, status: "pending"|"complete"|"failed",
  manifest_sha256, manifest_signature, signer_address,
  attestation_tx, attestation_at, eas_uid,
  parent_bundle_id, superseded_by,
  legal_hold: boolean, retention_until, created_at
}
Example prompts:
- "Show me the metadata for bundle ev_550e8400."
- "Check the status and notarization info of my evidence bundle."
- "Get me the details of bundle [ev_id] — is it complete?"
```

### `get_job_status`

- The name "get_job_status" says "get": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Poll the status of an async job (extract, indexing, batch). Free — no credits consumed. Use after add_document_to_collection or async extract to check when processing completes. Poll this endpoint in a loop until status is "complete" or "failed". Completed jobs include the bundle_id or result_json in the response.
Jobs are created when you POST /v1/extract with a webhook, or when add_document_to_collection triggers async indexing.
Returns: {
  id, type: "extract"|"extract_batch"|"index_collection",
  status: "queued"|"processing"|"complete"|"failed"|"cancelled",
  progress_pct: number (0–100), progress_message,
  bundle_id (when complete), result_json (when complete),
  error (when failed), created_at, completed_at
}
Example prompts:
- "Check the status of my indexing job job_550e8400."
- "Is my async extract job done yet?"
- "Poll job [job_id] — what is the current progress?"
```

### `get_quota`

- The name "get_quota" says "get": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Get current credit balance and plan details for your API key. Free — no credits consumed. Check this before running credit-consuming operations (extract, summarize, etc.) to avoid QUOTA_EXCEEDED errors. Returns plan tier, billing period, and usage breakdown.
Returns: {
  plan_id, billing_period (YYYY-MM),
  credits_used, credits_limit, credits_remaining,
  status: "active"|"suspended"
}
Example prompts:
- "How many credits do I have left this month?"
- "Check my current quota and plan status."
- "Am I going to hit my credit limit soon?"
```

### `list_collections`

- The name "list_collections" says "list": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
List all document collections owned by your API key. Free — no credits consumed. Use before search_collection or ask_collection when you need the collection ID. Supports pagination with limit and offset.
Returns: { collections: [{ id, name, created_at }] }
Example prompts:
- "List all my document collections."
- "Show me the collections I have created."
- "What collections do I own? List them."
```

### `qa_url`

- The description's first verb is "fetch": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Fetch a public HTTPS URL and answer a specific question about its content. Lean mode — no bundle stored. Use when you have a precise question about a web page. For a broad summary, use summarize_url. For multi-document Q&A, use ask_collection instead.
Returns: { url, answer, answer_cited: { value, confidence, citations[] }, confidence: "high"|"medium"|"low", truncated }
Example prompts:
- "What is the refund policy at https://docs.example.com/policy?"
- "Look at [URL] and tell me what the delivery terms are."
- "Answer this question based on the content of [URL]: [question]."
```

### `search_collection`

- The name "search_collection" says "search": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Semantic (vector) search across documents in a collection. Returns ranked text chunks with relevance scores. Free — no credits consumed. Use when you need raw matching chunks from a collection. For a synthesized cited answer from the same context, use ask_collection instead.
PREREQUISITE: Collection must be populated via add_document_to_collection and async indexing must complete (poll get_job_status) before results appear.
Returns: { results: [{ bundle_id, chunk_id, text, score: number (0–1), title? }] }
Example prompts:
- "Search my Q4 Contracts collection for mentions of liability cap."
- "Find the clause about data retention in my due diligence docs."
- "Search for revenue numbers across my quarterly reports."
```

### `summarize_document`

- The name "summarize_document" says "summarize": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Summarize document text into a prose summary and key points with citations. Use after extract_text or extract_url when you need a condensed understanding of a long document. For single-sentence Q&A, use qa_url instead. For extracting specific fields, use extract_structured.
Typical workflow: extract_text/extract_url → summarize_document.
Returns: {
  summary: string,
  key_points: string[],
  summary_cited: { value, confidence, citations[] },
  key_points_cited: [{ text, citations[] }],
  truncated: boolean,
  strategy: "full"|"truncated"|"chunked"
}
Example prompts:
- "Summarize this financial report and give me the key points."
- "What are the main takeaways from this document?"
- "Give me a concise summary of this 50-page report."
```

### `summarize_url`

- The name "summarize_url" says "summarize": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Fetch a public HTTPS URL and return a prose summary with key points. Lean mode — no bundle stored. Use when you need a condensed understanding of a web page. For raw text, use extract_url. For asking a specific question about a page, use qa_url.
Returns: { url, summary, key_points: string[], truncated: boolean, word_count }
Example prompts:
- "Summarize https://en.wikipedia.org/wiki/Artificial_intelligence for me."
- "Give me the key points from this blog post: [URL]."
- "What is this article about? Summarize [URL]."
```

### `translate_url`

- The description's first verb is "fetch": a word for reading.

Description, as the server wrote it:

```untrusted-server-text
Fetch a public HTTPS URL and return its content translated into a target language. Lean mode — no bundle stored. Use when you need to understand web content in a different language. For extracting raw untranslated text, use extract_url instead.
Returns: { url, translated_text, target_lang, truncated }
Example prompts:
- "Translate https://example.de/artikel into English for me."
- "Translate this German article into Spanish: [URL]."
- "Fetch [URL] and give me the French translation."
```

## Claude Code permissions

For `.claude/settings.json`, assuming the server is installed as `api`:

```json
{
  "permissions": {
    "allow": [
      "mcp__api__summarize_document",
      "mcp__api__search_collection",
      "mcp__api__extract_url",
      "mcp__api__summarize_url",
      "mcp__api__qa_url",
      "mcp__api__translate_url",
      "mcp__api__get_bundle",
      "mcp__api__get_job_status",
      "mcp__api__list_collections",
      "mcp__api__get_quota"
    ],
    "ask": [
      "mcp__api__extract_text",
      "mcp__api__extract_tables",
      "mcp__api__parse_invoice",
      "mcp__api__check_claims",
      "mcp__api__extract_structured",
      "mcp__api__verify_bundle",
      "mcp__api__create_collection",
      "mcp__api__ask_collection",
      "mcp__api__notarize_bundle",
      "mcp__api__verify_action_receipt",
      "mcp__api__add_document_to_collection"
    ],
    "deny": []
  }
}
```