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272,154 tools. Last updated 2026-07-08 07:09

"Enhancements for Claude Desktop App with Large Contexts and Long Documents" matching MCP tools:

  • Fetch one methodology playbook (markdown) by name. Start with `start-here`. Use `list_playbooks` to see everything published. Playbooks are living documents — re-fetch rather than caching long-term; the `changelog` playbook records dated methodology/data changes. Args: name: Playbook name as returned by `list_playbooks` (e.g. "start-here", "daily-workflow", "run-your-own-tournament", "exit-lab", "leakage-and-data-contract", "changelog"). Returns: {name, title, content} — content is markdown.
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  • Public observability snapshot for the fomox402 broker. WHAT IT DOES: returns aggregated MCP traffic + per-tool call telemetry. Read-only, no auth required, no side effects. WHEN TO USE: for dashboards, health checks, or to verify the broker is alive before a long autonomous run. The /v1/stats/mcp endpoint that backs this tool is also what powers https://bot.staccpad.fun/dashboard. RETURNS: { sessions: { active, last_24h, lifetime, median_duration_sec }, tools: [{ name, calls, errors, error_rate }], uptime_sec, broker_version }. VISIBILITY CAVEAT: only counts streamable-HTTP traffic to https://bot.staccpad.fun/mcp. Local stdio MCP clients (e.g. Claude Desktop running this file directly) are invisible to the broker DB and not reflected here. RELATED: list_agents (per-agent activity), get_me (your own stats).
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  • FOR CLAUDE DESKTOP ONLY (with filesystem access). For Claude.ai/web: Use create_upload_session instead - it provides a browser upload link. Upload local media to cloud storage, returning a public HTTPS URL. WHEN TO USE: • Instagram, LinkedIn, Threads, X: REQUIRED for local files before calling publish_content • TikTok: NOT NEEDED - pass local path directly to publish_content SUPPORTED FORMATS: • Images: jpg, png, gif, webp (max 10MB) • Videos: mp4, mov, webm (max 100MB) Returns { url: 'https://...' } for use in publish_content mediaUrl parameter.
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  • Validates a package of 2-20 related trade finance documents for cross-document consistency. Call this BEFORE approving any multi-document trade finance transaction or cross-border shipment -- at the moment a set of 2-20 related documents arrives from an external party and funds have not been released. Use this when your agent has received a full trade finance package — such as invoice, bill of lading, and certificate of origin together — and must verify all documents are consistent with each other before releasing funds. Returns PASS/FLAG/FAIL verdict per document with mismatch details. Cross-checks all documents for consistency across numeric values, party names, reference numbers, dates, and commodity descriptions. A single inconsistency in a trade finance document package may indicate fraud -- funds released on a mismatched package have no recovery path. Do not use as a substitute for check_document when only one document requires verification.
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  • 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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  • Offload a document conversion to Botverse — runs server-side in seconds, returns a download link, and frees you to continue with other tasks while it processes. Use this when the source document is at a public URL — direct download links and Dropbox / Google Drive / Box share links auto-resolve. OneDrive and SharePoint share links are unreliable (they often return a viewer page, not the file) — use a direct download URL for those. If you already have the content as a string, use convert_content instead — no upload step needed. Runs entirely server-side, so it works in sandboxed agent environments (claude.ai, Claude Desktop, Cursor) — the right route there for files too large for convert_content's 4 MB inline limit. Supported inputs: md, html, rst, txt, docx. Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx (tables extracted). Returns a job_id immediately. Poll get_job_status every 5s until 'complete', then get_output_content (inline, sandbox-safe) or get_download_url (S3 link). Flat fee $0.05 per file.
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Matching MCP Servers

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    A fake MCP server with 108 themed tools for testing Claude Desktop's handling of large toolsets and Amazon Bedrock AgentCore Gateway integration.
    Last updated
    15
    MIT
  • F
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    Enables Claude Code to send prompts to Claude Desktop using macOS automation and AppleScript. Supports conversation management and configurable response polling, though reading responses back is limited by Electron's accessibility APIs.
    Last updated
    2
    1

Matching MCP Connectors

  • Your coding agent writes the feature — let it test it too. Long Horizon runs real browser tests and produces shareable execution reports for confident feature delivery.

  • Persistent project context for Claude. IANA-registered .faf format.

  • List and filter issues from a single ACC project (limit 50 per call) via the APS Construction Issues API. When to use: The user or upstream agent needs to review open issues, count issues by status/priority, or look up an issue_id before calling acc_update_issue. E.g. 'show me all critical open issues on the Tower project'. When NOT to use: Do not use to fetch RFIs (use acc_list_rfis) or to search documents. APS scopes: data:read account:read. No write scope required. Rate limits: ACC Issues API ~100 req/min per app; results pageable (limit 50 here, max 200 upstream). For large projects, call once and filter client-side instead of looping. Errors: 401 (APS token expired — refresh); 403 (user lacks 'View Issues' permission on project or scope insufficient); 404 (project_id not found — verify 'b.' prefix and hub membership via acc_list_projects); 422 (invalid filter value — check status/priority spelling); 429 (rate limit — back off 60s); 5xx (ACC upstream — retry with jitter). Side effects: None. Read-only and idempotent.
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  • Reads the raw HTML source currently shown on a display so you can inspect or edit it and push it back with send_html. content_type 'idle' reads the default/fallback content instead. Responses are windowed for large documents: max_bytes (default 51200) and offset page through the source; the result reports totalBytes and truncated. Not for visual previews (use get_display_preview_url). Requires content scope.
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  • MANDATORY first step whenever the user attached an image in chat (or pointed at a local file on disk) and wants edit_image or image-to-video generation. Returns a signed PUT URL plus a file_id. How the bytes get uploaded depends on WHERE you run, and the discriminator is network access to the URL, not shell access: (a) Claude.ai (web, desktop, or mobile app): this tool renders an inline upload widget. The user drops the image into it; it uploads from their browser and pushes the file_id back automatically. Your code-execution sandbox has NO network route to the signed URL — a chat attachment sitting on the sandbox filesystem does NOT mean you can upload it. NEVER attempt curl/fetch/Python uploads from a sandbox and never investigate domain allowlists; just ask the user (one short sentence) to drop the image into the widget, then stop and wait. (b) Claude Code / a CLI with a real shell on the user's machine: run the ready-made curl PUT from the response text. Then call edit_image or generate_video with file_id=<returned id>. edit_image and generate_video do NOT accept base64 — calling them with raw image bytes WILL fail. This tool is the only working path for chat attachments. Set `purpose` to 'edit' or 'video' so the upload widget points the user at the right downstream tool.
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  • Complete one-shot setup: validates prerequisites, creates a controller VM + worker VMs, auto-creates a public HTTPS URL on port 7070, seeds a starter ROADMAP.md into the repo if absent, and returns the trigger token. Call this when a user says 'set up autocoding agents for my repo' or 'I want agents to work on my codebase'. HOW THE AGENT WORKS: each worker runs Claude Code inside the repo, implements one task, runs the test suite, and opens a pull request. It excels at focused, single-PR, testable units of work — add an endpoint, write tests for a module, fix a specific bug, add a UI page — and is poor at vague/large tasks, design decisions, or anything needing external credentials. TASK FORMAT (strict, one line each): `- [ ] **Title** — short description *(agent-ready)*` — the `- [ ]` checkbox, `**bold title**`, ` — ` separator, and `*(agent-ready)*` are ALL required; `##` headings and plain bullets are ignored. After this returns, the user needs to: (1) authorize the fleet by running the authorize.sh one-liner it returns (it runs `claude setup-token` for a long-lived token installed on the controller) — agents use the user's existing Claude Max/Pro subscription, NOT an API key. This is a shell command the USER runs in their own terminal; do NOT try to read or push the user's credentials yourself. The controller takes ~7 min to boot, so PREFER to poll get_agent_status until it reports the controller is reachable and present the authorize command only once it's ready — that way the user doesn't run it into a long wait. (The command also waits on its own, showing a live progress counter, so a user who runs it early is fine too.) (2) add well-scoped tasks in the format above to ROADMAP.md; (3) call trigger_agent_batch.
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  • Create a REAL LexVibe app in the user's account (replaces any YOUR_APP_ID placeholder). Returns a claim link: show it to the user so they can sign in and confirm — the link expires in 30 minutes. On confirmation LexVibe creates the app, scans the URL (if given), generates and hosts the legal documents. After the user confirms, call get_claim_status with the returned code to retrieve the real app id and install snippet. Provide at least `url` or `appName`.
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  • Compose a post with an attached image OR short MP4 video WITHOUT needing filesystem access on the agent's machine. This is the cross-surface alternative to `upload_media_from_path` — it works from claude.ai, ChatGPT, ANY agent surface, because the actual file upload happens in the user's browser, not the agent's process. USE WHEN: the user wants to share a photo or video and you're running anywhere that ISN'T local Claude Desktop (no filesystem access). Examples: claude.ai chat, ChatGPT with this MCP server, mobile web. In those contexts `upload_media_from_path` will fail. FLOW: (1) you call this tool with the post text + optional community, (2) tool returns `{ token, upload_url, expires_at }`, (3) show the upload_url to the user — they click it, sign in to caulo.ai (if not already), pick a file (JPEG/PNG/WebP up to 10 MB OR MP4 up to 50 MB and 30 s) from THEIR device, (4) when the upload moderation passes, the post is created and visible. For videos, moderation runs out-of-process and takes up to ~3 minutes — the upload page polls for the user; they just wait for it to complete. The link is single-use, 15-minute TTL, bound to the user — nobody else can use it even if it leaks. Return the upload_url to the user as a clickable link with a clear call-to-action like 'Click here to pick a photo or short video: <url>'. Do NOT auto-retry if the user doesn't click within 15 minutes — mint a new link instead.
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  • Reflect on recent thoughts and patterns. Analyzes recent activity to identify patterns, topics, and insights. Useful for understanding "what have I been thinking about?" By default, only returns user-created memories (not document chunks). Set include_documents=True to also include chunks from uploaded documents. ⚠️ EXPERIMENTAL: - Importance weighting in results not yet implemented. Importance scores are stored but don't affect ranking. Args: time_window: Time period to analyze ('recent', 'today', 'week', 'month', '1d', '7d', '30d', '90d') include_documents: Whether to include document chunks (default: False, only user memories) start_date: Filter memories created on or after this date (ISO 8601: '2025-01-01' or '2025-01-01T00:00:00Z') end_date: Filter memories created on or before this date (ISO 8601: '2025-01-09' or '2025-01-09T23:59:59Z') ctx: MCP context (automatically provided) Returns: Dict with analysis including top memories, active topics, patterns, insights, and any saved contexts (checkpoints) created in the window. Examples: >>> await reflect("recent") {'success': True, 'memories_analyzed': 50, 'active_topics': [...], 'contexts': [...], ...} >>> await reflect("week", include_documents=True) {'success': True, 'memories_analyzed': 150, ...} # includes document chunks >>> await reflect(start_date="2025-01-01", end_date="2025-01-07") {'success': True, 'memories_analyzed': 25, ...} # memories from first week of January
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  • Discover AXIS install metadata, pricing, and shareable manifests for commerce-capable agents. Free, no auth, and no mutation beyond read access. Example: call before wiring AXIS into Claude Desktop, Cursor, or VS Code. Use this when you need onboarding and ecosystem setup details. Use search_and_discover_tools instead for keyword routing or discover_agentic_purchasing_needs for purchasing-task triage.
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  • Public observability snapshot for the fomox402 broker. WHAT IT DOES: returns aggregated MCP traffic + per-tool call telemetry. Read-only, no auth required, no side effects. WHEN TO USE: for dashboards, health checks, or to verify the broker is alive before a long autonomous run. The /v1/stats/mcp endpoint that backs this tool is also what powers https://bot.staccpad.fun/dashboard. RETURNS: { sessions: { active, last_24h, lifetime, median_duration_sec }, tools: [{ name, calls, errors, error_rate }], uptime_sec, broker_version }. VISIBILITY CAVEAT: only counts streamable-HTTP traffic to https://bot.staccpad.fun/mcp. Local stdio MCP clients (e.g. Claude Desktop running this file directly) are invisible to the broker DB and not reflected here. RELATED: list_agents (per-agent activity), get_me (your own stats).
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  • Drive a headless Chromium against a URL and return a screenshot for each requested viewport (mobile / tablet / desktop). Optional clickPaths lets you grab the state behind a sequence of clicks (e.g. ['Sign in', '#email', 'Continue']). Pricing: 1 credit per single viewport, 5 credits for the desktop+tablet+mobile triple (otherwise 1 × viewport count). Output: signed Spaces URLs valid for 7 days. Use this for marketing screenshots, design QA, regression-watch baselines — anything where you need pixels without a full AI test.
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  • Get a humantaste.app URL where a human can place a consult_domain_expert order from a browser (Connect MetaMask, pay $15 USDC on Base, session created). Use this when your MCP client has no wallet integration (Claude Desktop, generic chat UIs). The URL is pre-filled with the brief you pass in; the user just opens it, reviews, connects a wallet, and pays. Returns the payment URL and the price. Free.
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  • Get a presigned HTTPS URL to download the completed output file. Call after get_job_status returns 'complete'. URL expires in 24 hours. NOTE: fetching this URL is a direct S3 download, which is BLOCKED in sandboxed agent environments (claude.ai, Claude Desktop, Cursor). If you are in a sandbox, use get_output_content instead to receive the bytes inline over the tool channel.
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  • Convert a document inline — pass the content directly as a string (or base64 for binary inputs like .docx). PREFERRED route for documents, and the one to use in sandboxed agent environments (claude.ai, Claude Desktop, Cursor): it runs entirely server-side, so it never needs the S3 upload those sandboxes block. Limit: up to 4 MB of content — already huge (a 500-page book is ~1 MB of text). For anything larger, use convert_from_url with a public URL. Supported inputs: md, html, rst, txt (plain text), docx (base64). Supported outputs: docx (Word), pdf, html, txt, md, rst, xlsx. Returns a job_id — poll get_job_status until 'complete', then get_output_content (inline bytes, sandbox-safe) or get_download_url (S3 link). Flat fee $0.05 per file. TIP: if you have shell access and are NOT sandboxed (e.g. a local coding agent), the `botverse` CLI (`npx botverse convert <file> --to <fmt>`) is faster for local files — it streams from disk instead of re-emitting the content through the model.
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  • Obtain the CivilQuants customer-side document pipeline — the toolkit the document-heavy skills (tender review, geotechnical / geo-environmental interpretation) use to chunk a tender pack and render a Word pack on the user's machine. Returns the self-unpacking chunking package, the pipeline discipline, and the python-docx render helpers. Universal (free + paid). NOTE: running the pipeline over real documents requires a code-execution client (Claude Code / Codex / VS Code) — a chat connector can read the toolkit but cannot execute it. The full kit is large (~60 KB); pass component='chunking'|'discipline'|'render' for one part (~20 KB each), or omit it for the whole kit.
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