"A server for finding PDF documents and files" matching MCP tools:

• confirm_datasheet_upload

  sheetsdata-mcp

  Confirm a datasheet upload started via request_datasheet_upload. Pass the upload_token you got back from the request step. The server downloads the uploaded bytes, re-hashes to verify integrity, validates that it's a real PDF with the MPN on the first page, creates the private Document + Component records, charges the upload fee (50¢), and queues extraction. Success response: document_id, mpn, sha256, file_size_bytes, status='pending'. Poll check_extraction_status with the MPN to wait for extraction to finish (30s-2min typically). Failure modes: - 'upload_not_found' — no bytes at the upload URL yet. Retry your curl upload. - 'sha256_mismatch' — uploaded bytes hash differs from expected_sha256. Re-compute the hash and re-request. - 'invalid_pdf' — bytes aren't a parseable PDF. No charge. - 'mpn_not_in_pdf' — MPN (or its stem) isn't on the first page. Either you uploaded the wrong file or it's a scanned image-only PDF. No charge. - 'token_expired' — upload token is older than 15 minutes. Restart via request_datasheet_upload.

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• files_read

  dialogbrain

  Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.

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• cover_letter_tool

  Workopia

  Write a cover letter for a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's JD and the candidate's background, plus writing instructions. YOU (the model) then WRITE the cover letter (250–350 words, specific to the role, mapping the candidate's real achievements to the JD — never fabricate). STEP 2: call this tool again with action:'save', cover_letter_text:<your letter>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user asks for a cover letter for a specific job. Resolving job_id (same rules as tailor_resume_tool / job_detail_tool): pass the **Job Id** value from the most recent prior search/refine result VERBATIM; no placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / json_resume / user_profile.

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• corpus.search

  AssayChain — Mineral Intelligence (USGS and Field Runs)

  Free lexical search (BM25-lite) across all 199 EAS-attested files: 20 USGS critical-mineral commodity benchmarks + 179 US/MX mining district records. Returns the top matching documents with on-chain provenance UIDs (attestation_uid, source_cid), IPFS-pinned source, and a relevant snippet. Use this to discover which attested records cover a topic, then either (a) call benchmark.commodity / district.history for paid full data, or (b) call the paid REST endpoint POST /api/ask for a Groq-grounded synthesised answer with inline citations ($0.10 USDC via x402 on Base).

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• request_datasheet_upload

  sheetsdata-mcp

  Request a signed URL to upload a datasheet PDF for a component whose datasheet we don't have. Use this when search_parts / get_part_details / prefetch_datasheets return datasheet_status='no_source' (and a retry didn't help) or 'unsupported'. Free — the upload fee is only charged on confirm_datasheet_upload after we validate the file. Flow (3 steps): 1. Call request_datasheet_upload with the MPN, the file's SHA-256, and its byte size. You get back an upload_url, upload_method ('PUT'), upload_headers, and an opaque upload_token. 2. Upload the PDF directly to the returned URL with curl: `curl -X PUT -H 'Content-Type: application/pdf' --data-binary @file.pdf "$UPLOAD_URL"` (add any headers from upload_headers). 3. Call confirm_datasheet_upload with the upload_token. Server verifies the bytes, re-hashes, checks for the MPN on the first page, charges the upload fee (50¢), and queues extraction. Returns document_id + status='pending'. Validation rules (checked at confirm time, refunded on failure): - File must be a valid PDF (magic bytes + parseable). - Actual SHA-256 must match expected_sha256. - Actual byte size must match size_bytes (±0). - MPN or its core stem must appear in the first page text (catches wrong-file uploads). Scanned image-only PDFs will fail this check — upload a text-based PDF. - Max 50MB per file. No dev-kit manuals / BOB schematics / app-notes as datasheets — use the matching MPN's actual datasheet. Uploaded datasheets are scoped to your organization (private). They satisfy read_datasheet, search_datasheets, check_design_fit, and analyze_image for your org's tokens only. Tokens expire after 15 minutes. If upload fails or times out, just call request_datasheet_upload again.

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• knowledge_query

  DialogBrain

  Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.

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• atlas_download_report

  CareerProof MCP

  Download a completed report as PDF. Returns base64-encoded PDF content. Confirm report status='completed' via atlas_get_report(report_id) first. report_id from atlas_start_report response or atlas_list_reports. Free.

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• brand_audit_get_report

  dns

  Fetch the result JSON for a completed brand audit. With `target` set, returns the per-target CheckResult; without, returns the audit-level aggregate. Returns notReady when polling an in-flight audit. When a rendered PDF sidecar exists and the R2 binding is configured, metadata includes a signed PDF URL; completed targets without a PDF URL include pdfPending so callers can poll again.

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• lemma_query_verified_attributes

  mcp

  Query cryptographically verified attributes from Lemma. Use this as the primary tool for finding documents whose attributes match given conditions (e.g., "subject's birthYear lt 2008"). Returns { results: Array<{ docHash, schema, issuerId, subjectId, attributes, isVerified, proof?: { status, circuitId, chainId }, disclosure? }>, hasMore }. The MCP layer enriches each item with an `isVerified` flag derived from `proof.status` (true when status is 'verified' or 'onchain-verified'). Use lemma_get_proof_status to monitor a specific proof; use lemma_get_schema to interpret the keys returned in `attributes`.

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• files_read

  DialogBrain

  Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.

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• knowledge_query

  dialogbrain

  Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.

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• render_mermaid

  Diagrams MCP

  Render a Mermaid diagram definition and return the image with metadata. The definition should be valid Mermaid syntax (e.g. flowchart, sequence, class, ER, state, or Gantt diagram). Returns a list of content blocks: the rendered image plus a JSON text block with metadata including a mermaid.live edit link for opening the diagram in a browser editor. Args: definition: Mermaid diagram definition text. filename: Output filename without extension. format: Output format — ``"png"`` (default), ``"svg"``, or ``"pdf"``. download_link: If True, return a temporary download URL path (/images/{token}) that expires after 15 minutes; if False, return inline image bytes. Defaults to True (URL) — set ``DIAGRAMS_INLINE_DEFAULT=true`` on the server to flip the default. SVG/PDF and PNGs larger than the inline limit always use a download link.

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• xmp4_grep

  xmp4 — Semantic code knowledge for your stack

  Server-side regex text search over indexed project source files. Free tier: requires file_path (single file). Premium tier (XMP4_PREMIUM_GREP_WALK=true): allows file_glob multi-file walk. Prefer xmp4_tests_for/xmp4_usages for SCIP symbols — grep is for text not indexed (comments, literals, config keys).

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• files_get_base64

  DialogBrain

  Download one or more files server-side and return their content as base64-encoded strings. Use this to inspect images, PDFs, or any binary file attached to messages when you cannot access presigned S3 URLs directly. Supports up to 5 files per call, max 15 MB each. For large files batch in groups of 1-2 to avoid oversized responses.

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• generate_pdf_from_text

  Toolora

  Use this tool when the user wants to save, export, or share your output as a PDF document. Triggers: 'save this as a PDF', 'export this to PDF', 'create a PDF report', 'generate a document I can download', 'turn this into a file'. Supports # headings, ## subheadings, - bullet lists, and plain paragraphs. Returns a base64-encoded PDF. Proactively offer this after generating reports, summaries, action plans, or any long-form content the user will want to keep.

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• files_get_base64

  dialogbrain

  Download one or more files server-side and return their content as base64-encoded strings. Use this to inspect images, PDFs, or any binary file attached to messages when you cannot access presigned S3 URLs directly. Supports up to 5 files per call, max 15 MB each. For large files batch in groups of 1-2 to avoid oversized responses.

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• render_diagram

  Diagrams MCP

  Render a mingrammer/diagrams Python snippet to PNG and return the image. The code must be a complete Python script using `from diagrams import ...` imports and a `with Diagram(...)` context manager block. Use search_nodes to verify node names and get correct import paths before writing code. Read the diagrams://reference/diagram, diagrams://reference/edge, and diagrams://reference/cluster resources for constructor options and usage examples. Args: code: Full Python code using the diagrams library. filename: Output filename without extension. format: Output format — ``"png"`` (default), ``"svg"``, or ``"pdf"``. download_link: If True, return a temporary download URL path (/images/{token}) that expires after 15 minutes; if False, return inline image bytes. Defaults to True (URL) — set ``DIAGRAMS_INLINE_DEFAULT=true`` on the server to flip the default. SVG/PDF and PNGs larger than the inline limit always use a download link.

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• pictify_render_multi_page_pdf

  mcp

  Generate a multi-page PDF from a template by providing multiple sets of variables. Each variable set produces one page in the final document. Supports 1-100 pages per PDF. Common use cases: bulk invoice generation, certificate batches for events/courses, multi-page reports, product catalogs, and employee ID cards. WORKFLOW: Call pictify_get_template_variables first to discover available variables, then provide an array of variable sets (one per page). Returns a single combined PDF URL. For generating separate image files per set, use pictify_batch_render instead.

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• images_prepare_upload

  Roboflow (Official)

  Get an upload URL to upload a single image to a project. Returns a pre-built upload URL and instructions. The caller must perform the actual upload using curl since the MCP server cannot access local files. This endpoint uploads images only. To add annotations, call annotations_save with the image ID from the upload response. For bulk uploads with annotations, use images_prepare_upload_zip.

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• get_top_funding_rates

  MarketMCP

  Top Hyperliquid perps ranked by absolute funding rate, with OI and annualized yield. Useful for finding the most overcrowded longs/shorts and carry opportunities.

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