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556,582 tools. Updated 2026-09-13 05:52

"Integrating Claude Desktop with a Local LLM using the LMStudio API" matching MCP tools:

  • 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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  • 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 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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  • Google PageSpeed Insights report for a URL: Lighthouse performance/accessibility/SEO scores and Core Web Vitals (LCP, CLS, INP, FCP, TTFB), with lab and field (CrUX) data. Defaults to mobile; pass strategy=desktop for the desktop profile. Subject to a per-user daily cap (50/day) and a service-wide daily cap; successful responses are cached for 24h.
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  • Record what happened after using a service: success/failure outcome, feedback, API change events, or qualitative experience. Data is saved to this installation's LOCAL database only (improves local recovery hints and stats) — nothing is sent to KanseiLink unless you separately opt in to sharing. PII is auto-masked before storage. This is step 4 of the standard flow: search_services → lookup → (execute) → report.
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Matching MCP Servers

Matching MCP Connectors

  • Validate ClaudeBot and Claude-SearchBot IP addresses. Remote MCP validate_ip tool.

  • Let ChatGPT, Claude & Cursor use your Mac: email, calendar, iMessage, Teams, files. Local, free.

  • Compare multiple LLM responses to the same prompt and detect inconsistencies using Jaccard word-overlap similarity and fact drift (number comparison). Fast, deterministic, no API key needed. Limitations: relies on surface-level word matching — "Paris is the capital of France" vs "Paris is the French capital" may score low despite semantic equivalence. For true semantic consistency, use run_semantic_tests with embedding mode. Essential for determinism testing.
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  • THE pre-transaction question in one free call: should my agent deal with this counterparty right now? Returns proceed / caution / reject with reasoning. Liveness-aware: an agent with no public activity signal in 30+ days never gets a clean proceed, even if well-ranked. Use before paying, delegating to, or integrating any agent. Deeper analysis (full risk decomposition, history, signed attestation) is x402/Pro priced — pointers included in the response.
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  • Lists the Slack workspaces (teams) the user has connected in Slack Desktop. Start here for Slack — the workspace id it returns is what slack_list_channels / slack_read_channel_messages / slack_search_messages need. Reads from the local IndexedDB cache — no token needed. Only workspaces that have been synced to disk are returned.
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  • List the runtimes generate_runtime_config supports (Claude Desktop, Cursor, VS Code, agent frameworks, …), with each one's config path. Enumerate these instead of guessing runtime slugs.
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  • Performs web searches using the Brave Search API and returns comprehensive search results with rich metadata. To chain into local-POI enrichment, pass `result_filter=locations` and feed the resulting `locations.results[].id` values into `brave_local_search`. To chain into the AI summarizer, pass `summary=true` and feed the returned `summarizer.key` into `brave_summarizer`.
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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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  • Interactive single-site design-conditions explorer. Returns full ASHRAE design conditions + diurnal chart for the requested scenario. In MCP Apps-capable hosts (Claude Desktop, ChatGPT, VS Code, Goose), the response renders as a widget with sliders for SSP / year / percentile / UHI — dragging a slider re-calls this tool live. Use when a user wants to interactively tune a single site. For multi-site comparison, use analyze_weather(urls=[...]) instead. Defaults to present-day TMY (no morph) — pass ssp+year for future scenarios. P75 default percentile is design-realistic; P50 underestimates the tail. No auth required.
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  • Connect Signal to Local MCP. Reports whether Signal Desktop is installed and signed in, and tells you exactly what to do next — install Signal, or open it and link your phone. (Signal links inside its own desktop app, so the QR is shown there, not here.) Once you're signed in, signal_list_chats / signal_read_messages work. If Signal is already connected, it just reports that.
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  • Compress retrieved memories using a hybrid approach (extractive + LLM). First searches Hipocampo (SSC v1.0), then compresses the top-k results: - method="extractive": sentence-level keyword relevance (fast, no API cost) - method="llm": summarization via NVIDIA NIM (highest quality, API cost) - method="hybrid" (default): uses LLM for technical/code content, extractive for generic text Use this tool BEFORE sending context to another LLM to reduce prompt size while preserving critical information. Args: query: Natural language search query. k: Number of memories to retrieve (default 5, max 20). method: Compression method: "hybrid" (default), "extractive", or "llm". target_token: Target token count (-1 = auto, based on content). include_metadata: Include per-memory details in output. budget_ratio: Scale factor for auto-estimated tokens (default 1.0). Returns: Compressed context as plain text with compression statistics. Includes: compressed text, original/compressed char counts, ratio, latency.
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  • Calculation, not advice. Verify with a professional before acting. Returns metadata about the running Senaro MCP server: version, contract version, build commit, build timestamp, and the full list of supported tools. Call this once per session before drafting any content to verify the running process is not stale after a deploy. Idempotent, no side effects, < 50 ms. If server_version is below the minimum required by your skill, STOP and ask the user to restart Claude Desktop.
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  • Return the finished output of a completed job INLINE as base64 — no S3 download. Use this in sandboxed agent environments (claude.ai, Claude Desktop, Cursor) where fetching a get_download_url link is blocked; it delivers the bytes over the same tool channel that always works. Call after get_job_status returns 'complete'. Limited to 4 MB outputs — for larger files use get_download_url (and a non-sandboxed environment, or add the S3 host to your egress allowlist).
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  • Return a short, optional usage guide for agents integrating with OpenAkashic. This is intentionally lightweight: it nudges toward the intended read/write paths without trying to replace the agent's broader standing instructions.
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  • Browse the Wix REST API documentation menu hierarchy. Alternative to SearchWixRESTDocumentation - use this to explore and discover APIs by navigating the menu structure instead of searching by keywords. - Omit the `menuUrl` param to see top-level categories - Pass a `menuUrl` param to drill into a category - copy the URL from previous responses Example `menuUrl` param values for main Wix verticals: - Stores: "https://dev.wix.com/docs/api-reference/business-solutions/stores" - Bookings: "https://dev.wix.com/docs/api-reference/business-solutions/bookings" - CMS: "https://dev.wix.com/docs/api-reference/business-solutions/cms" - CRM: "https://dev.wix.com/docs/api-reference/crm" - eCommerce: "https://dev.wix.com/docs/api-reference/business-solutions/e-commerce" - Events: "https://dev.wix.com/docs/api-reference/business-solutions/events" - Blog: "https://dev.wix.com/docs/api-reference/business-solutions/blog" - Pricing Plans: "https://dev.wix.com/docs/api-reference/business-solutions/pricing-plans" - Restaurants: "https://dev.wix.com/docs/api-reference/business-solutions/restaurants" - Media: "https://dev.wix.com/docs/api-reference/assets/media" - Site Properties: "https://dev.wix.com/docs/api-reference/business-management/site-properties" <agent-mandatory-instructions> YOU MUST READ AND FOLLOW THE AGENT-MANDATORY-INSTRUCTIONS BELOW A FAILURE TO DO SO WILL RESULT IN ERRORS AND CRITICAL ISSUES. <goal> You are an agent that helps the user manage their Wix site. Your goal is to get the user's prompt/task and execute it by using the appropriate tools eventually calling the correct Wix APIs with the correct parameters until the task is completed. </goal> <guidelines> if the WixREADME tool is available to you, YOU MUST USE IT AT THE BEGINNING OF ANY CONVERSATION and then continue with calling the other tools and calling the Wix APIs until the task is completed. **Exception:** If the user asks to create, build, or generate a new Wix site/website, skip WixREADME and: - If the user **explicitly** mentions a template, Wix Studio, or headless → call CreateWixBusinessGuide directly. - Otherwise → call the WixSiteBuilder tool directly. **Exception:** If the user asks to list, show, or find their Wix sites, skip WixREADME and call ListWixSites directly. **Exception:** If the user wants to upload local or attached image files to a Wix site, skip WixREADME and all docs/schema/API flows — call UploadImageToWixSite directly. Do NOT use ExecuteWixAPI, SearchWixAPISpec, or any Media Manager REST API for image uploads. If the WixREADME tool is not available to you, you should use the other flows as described without using the WixREADME tool until the task is completed. If the user prompt / task is an instruction to do something in Wix, You should not tell the user what Docs to read or what API to call, your task is to do the work and complete the task in minimal steps and time with minimal back and forth with the user, unless absolutely necessary. </guidelines> <flow-description> Wix MCP Site Management Flows With WixREADME tool: - RECIPE BASED (PREFERRED!): WixREADME() -> find relevant recipe for the user's prompt/task -> read recipe using ReadFullDocsArticle() -> call Wix API using CallWixSiteAPI() based on the recipe - CONVERSATION CONTEXT BASED: find relevant docs article or API example for the user's prompt/task in the conversation context -> call API using CallWixSiteAPI() based on the docs article or API example - EXAMPLE BASED: WixREADME() -> no relevant recipe found for user's prompt/task -> BrowseWixRESTDocsMenu() or SearchWixRESTDocumentation() -> find relevant method -> read method article using ReadFullDocsArticle() to get method code examples -> call API using CallWixSiteAPI() based on the method code examples - SCHEMA BASED, FALLBACK: WixREADME() -> no relevant recipe found for user's prompt/task -> BrowseWixRESTDocsMenu() or SearchWixRESTDocumentation() -> find relevant method -> read method article using ReadFullDocsArticle() -> no method code examples found -> inspect the method schema using SearchWixAPISpec or ReadFullDocsMethodSchema -> call API using CallWixSiteAPI() based on the schema Without WixREADME tool: - CONVERSATION CONTEXT BASED: find relevant docs article or API example for the user's prompt/task in the conversation context -> call API using CallWixSiteAPI() based on the docs article or API example - METHOD CODE EXAMPLE BASED: BrowseWixRESTDocsMenu() or SearchWixRESTDocumentation() -> find relevant method -> read method article using ReadFullDocsArticle() to get method code examples -> call API using CallWixSiteAPI() based on the method code examples - FULL SCHEMA BASED: BrowseWixRESTDocsMenu() or SearchWixRESTDocumentation() -> find relevant method -> read method article using ReadFullDocsArticle() -> no method code examples found -> inspect the method schema using SearchWixAPISpec or ReadFullDocsMethodSchema -> call API using CallWixSiteAPI() based on the schema </flow-description> </agent-mandatory-instructions>
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  • Get instructions for setting up AI Note MCP in Claude Desktop, Cursor, or other MCP clients. No authentication required.
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  • Compute text similarity using local algorithms (Bag of Words, TF-IDF, Character N-grams). No API key needed — runs entirely in-process. NOT real embeddings: for true semantic similarity with vector embeddings, use run_semantic_tests with mode="embeddings" and your OpenAI API key. Supports single pair or batch mode with pipe-separated pairs. Useful for RAG retrieval testing, semantic search evaluation, and text deduplication.
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