Skip to main content
Glama
306,388 tools. Last updated 2026-07-26 21:24

"Information about FAISS (Facebook AI Similarity Search)" matching MCP tools:

  • Hybrid search — combines keyword + semantic search via RRF. Uses Reciprocal Rank Fusion (RRF) to merge exact-word results with meaning-based results. **This is the recommended tool for "discourses about X" / concept queries**, because the semantic side catches suttas that discuss a concept using different vocabulary (e.g. some mindfulness-of-breathing suttas use `assasati/passasati/dīghaṁ` instead of `ānāpānassati`). 💡 **Hints for the AI client:** - English queries usually work best (e.g. `mindfulness of breathing`) because the embedding model is multilingual but EN-primary. - Thai stop-word handling is weak. If a Thai query underperforms, the AI client should translate to Pāli/English first (see server instructions). - The default `limit=5` is often too small for a topic survey — use `limit=15-20` (max 20) for good coverage. - Ranking is by similarity, NOT canonical importance — locus classicus suttas (e.g. MN118, DN22) may rank below smaller suttas that happen to use the exact vocabulary. Treat results as a starting point, then call `get_sutta` for the canonical references.
    Connector
  • Community-discourse search via parallel.ai with optional platform filtering. Returns synthesized text excerpts plus direct URLs to real Reddit threads, X posts from named operators, Substack essays, LinkedIn posts, Facebook posts. Use for: "what are practitioners saying about X", recurring themes in founder voice, multi-platform discourse mapping, verbatim quotes from named individuals. Per Phase 3.5 empirical A/B (Docs/solutions/architecture-decisions/search-backend-architecture-jun04.md): this tool SOLVES the Reddit/X retrieval gap that perplexity_search fundamentally couldn't fill. Optional platforms[] to restrict (e.g. ["reddit","x","substack"]). Per social-listening-synthesis §3 sample ≥3 platforms per brief.
    Connector
  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
    Connector
  • Fetch public business page information from Facebook. Returns page details including name, category, address, phone, website, ratings, reviews, followers, and cover/profile photos. Provide exactly one of page_id, username, or url — prefer url when the user pasted any Facebook link (including mobile share links), since the tool resolves the canonical page automatically.
    Connector
  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
    Connector
  • Test a message against an AI filter to check whether it would match. This tool embeds the provided message using Voyage AI and computes the cosine similarity between the message vector and the filter's stored reference vector. It returns the similarity score, whether the message would match (similarity >= threshold), and the filter's threshold value. Use this to: - Verify a filter works as intended before using it in a trigger - Tune the threshold by testing borderline messages - Debug why a message did or did not match a filter in production Returns: {similarity: float, matched: bool, threshold: float} Note: This tool calls the Voyage AI embedding API to embed the test message.
    Connector

Matching MCP Servers

  • A
    license
    -
    quality
    D
    maintenance
    MCP server for Facebook Pages that allows creating, scheduling, and deleting posts, managing comments, and retrieving Page insights using the Facebook Graph API.
    Last updated
    3
    MIT
  • -
    license
    -
    quality
    C
    maintenance
    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
    Last updated

Matching MCP Connectors

  • Returns structured information about what the Recursive platform includes: features, AI model details, supported integrations, and what's included at every tier. Use for systematic feature comparison.
    Connector
  • Semantic search across the full corpus — every place dossier, corridor signal, meeting reading, and named-pattern brief. Returns results ranked by cosine similarity in a 1024-dimensional embedding space (Voyage AI 4 + Supabase pgvector). Use when the agent does not know the canonical entity slug or named-pattern title in advance — the search returns the readings whose semantic structure best matches the natural-language query, with type, title, similarity, and resolved URL per hit. Threshold 0.55, top 12.
    Connector
  • Top-K Voyager skill retrieval by description similarity. Embeds the query (e.g. the candidate goal text) via Cloudflare Workers AI and asks agents.search_skills for the K closest skills by cosine distance. Caller invokes the first match if distance < 0.25 (~ similarity > 0.75); else falls through to generating fresh actions.
    Connector
  • [tourradar] Search for tours by title using AI-powered semantic search. Returns a list of matching tour IDs and titles. Use this when you need to look up a tour by name. When you know tour id, use b2b-tour-details tool to display details about specific tour
    Connector
  • [tourradar] Search tour reviews using AI-powered semantic search. Requires tourIds to scope results to specific tours. Use this when the user asks about reviews, feedback, or experiences for specific tours. Combine with an optional text query to find reviews mentioning specific topics (e.g., 'food', 'guide', 'accommodation'). When you don't have tour IDs, use vertex-tour-search or vertex-tour-title-search first to find them.
    Connector
  • Test a message against an AI filter to check whether it would match. This tool embeds the provided message using Voyage AI and computes the cosine similarity between the message vector and the filter's stored reference vector. It returns the similarity score, whether the message would match (similarity >= threshold), and the filter's threshold value. Use this to: - Verify a filter works as intended before using it in a trigger - Tune the threshold by testing borderline messages - Debug why a message did or did not match a filter in production Returns: {similarity: float, matched: bool, threshold: float} Note: This tool calls the Voyage AI embedding API to embed the test message.
    Connector
  • AI summary of a Facebook video or post. Costs ~4 credits; cached results are free, failures are never charged.
    Connector
  • Search SearchShop AI's Research Notes blog — data studies, playbooks, and field notes on agentic commerce (AI attribution, MCP, AI catalog accuracy, ChatGPT ads). Returns matching articles with titles, summaries, and URLs. Use when asked what SearchShop AI has written or published about a topic.
    Connector
  • Search contacts using natural language AI-powered semantic search. Finds contacts based on the meaning of their notes — skills, services, schedules, preferences, etc. Returns ranked results with relevance scores and AI-generated match reasons.
    Connector
  • Enrich a B2B company profile with structured firmographic, technographic, intent, and contact data. This tool should be called when an AI agent needs to gather detailed information about a company before crafting a personalized outreach, generating a lead score, or making a sales recommendation.
    Connector
  • List the Meta (Facebook/Instagram) ad accounts on this company's connection, with status, currency, lifetime spend, and spend cap. Use first when the user asks about their FB/IG ads — the returned id feeds list_ad_campaigns and get_ads_performance. Routing: Meta/FB/IG ads questions → start here to find the ad account
    Connector
  • [SDK Docs] Search across the documentation to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about Docs, find specific documentation, understand how features work, or locate implementation details. The search returns contextual content with titles and direct links to the documentation pages.
    Connector
  • Scrape a page into clean structured JSON using a named Crawlbase scraper — skip HTML parsing entirely. Common scraper names: "amazon-product-details", "amazon-serp", "google-serp", "facebook-page", "facebook-profile", "instagram-profile", "instagram-post", "linkedin-profile", "linkedin-company", "tiktok-profile", "ebay-product", "walmart-product-details", "github-repository", "generic-extractor". Full catalog: https://crawlbase.com/docs/scrapers/ — social-media scrapers (Facebook/Instagram/LinkedIn) work best with your JavaScript token. Example: crawlbase_structured({ url: "https://www.amazon.com/dp/1098145356", scraper: "amazon-product-details", _apiKey: "your-crawlbase-token" })
    Connector
  • Generate an AI-powered similarity key for individual/person name matching. Handles variations like 'Bob Smith', 'Robert Smith', 'Smith, Robert J.' producing the same key. Cost: $0.01 USDC via x402.
    Connector