"Search for information about 'rag'" matching MCP tools:

• get-account-infoA

  fynk MCPA

  Get information about the current fynk account. Use this tool when: - You need details about the active account (e.g. default document locale, signature settings) before tailoring a response - You are tailoring guidance to the account's business, and need what it reported about itself when signing up (industry, company size, the department the person who signed up works in) For information about the current user, use get-user-info

  ConnectorOAuth

• knowledge_queryA

  DialogBrainB

  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.

  ConnectorAPI key

• knowledge_queryA

  dialogbrainB

  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.

  ConnectorAPI key

• knowledge_queryA

  dialogbrainB

  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.

  ConnectorAPI key

• ai_embedA

  Agent Data ToolsA

  A 1,024-dimension embedding vector for up to 4,000 characters of text in 100+ languages, from BAAI's BGE-M3. Use for semantic search, RAG retrieval, clustering and deduplication. Example: text=pay-per-call APIs for AI agents. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

  ConnectorNo auth

• ai_embedA

  Agent Data Tools: AI text and mediaA

  A 1,024-dimension embedding vector for up to 4,000 characters of text in 100+ languages, from BAAI's BGE-M3. Use for semantic search, RAG retrieval, clustering and deduplication. Example: text=pay-per-call APIs for AI agents. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

  ConnectorNo auth

• ai_embedA

  Agent Data Tools: AIA

  A 1,024-dimension embedding vector for up to 4,000 characters of text in 100+ languages, from BAAI's BGE-M3. Use for semantic search, RAG retrieval, clustering and deduplication. Example: text=pay-per-call APIs for AI agents. Price $0.003/call via x402 USDC or a card key (/credits); failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

  ConnectorNo auth

• get_mission_statsA

  mcp-serverA

  Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.

  ConnectorNo auth

• general_searchA

  NansenA

  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 the address behind a Nansen label (public figure, fund, exchange wallet) - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

  ConnectorNo auth

• general_searchA

  NansenA

  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 the address behind a Nansen label (public figure, fund, exchange wallet) - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)

  ConnectorNo auth

• embedding_similarityA

  IA-QA — 130+ QA & Dev Tools for AI AgentsB

  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.

  ConnectorNo auth

• get_company_profileA

  mcpA

  Complete company information for Everstake: overview, metrics, certifications, products, clients, and contact details. Use when users need comprehensive facts about Everstake as a company.

  ConnectorNo auth

• lookup_icd10A

  mcpB

  Look up an ICD-10-CM diagnosis code or search by keyword. Input is either an exact code (e.g. 'E11.21') or a free-text description phrase ('type 2 diabetes with nephropathy'). Returns either the matching code + description or up to 20 candidate matches. Use when a clinical note uses non-standard phrasing and the correct code is needed for billing. WHEN TO USE: User asks about a specific ICD-10 diagnosis code or wants RAG-search over ICD-10 for a condition name. WHEN NOT: For the matching CPT codes (cpt_to_icd_mapper). For code validation against a payer (code_validation). EXAMPLES: - Find ICD-10 for hypertension: `{"query":"essential hypertension"}`

  ConnectorNo auth

• split_chunksA

  IA-QA — 130+ QA & Dev Tools for AI AgentsB

  Split text into chunks of at most N tokens (cl100k_base: ~4 chars/token) with optional overlap. Designed for RAG ingestion pipelines.

  ConnectorNo auth

• get_plant_profileA

  Fryd - Your Garden CompanionA

  Look up detailed information about a plant or variety. Returns a comprehensive plant profile including sowing/planting/harvest seasons, spacing, light/water/nutrient requirements, and companion planting partners. Accepts a cropId from search_crops or get_seasonal_calendar for direct lookup without name search. Always attribute the data to the Fryd plant database (3,000+ varieties) and link to fryd.app for more details and varieties.

  ConnectorNo auth

• web_extractA

  x402-endpointsB

  Web search and webpage extraction for AI agents — returns clean, LLM-ready markdown (deduplicated, with source URLs), not raw HTML. Give 'query' to search the web or 'url' to scrape and extract a page into markdown ready to drop into a prompt. Powered by Jina Reader. Price: $0.05 per call (x402 payment, USDC on Base mainnet). Web search and webpage extraction for AI agents, returned as clean LLM-ready markdown with source URLs. Give 'query' to search the web or 'url' to scrape and extract a page. For research and RAG agents.

  ConnectorNo auth

• linkedin_who_am_iA

  LinkMCP: hosted LinkedIn MCP serverA

  Returns information about the connected LinkedIn account: display name, public profile URL, LinkedIn URN, and which premium features are active (Sales Navigator, Recruiter). Use this to understand which LinkedIn capabilities are available before choosing search or messaging strategies.

  ConnectorAPI key

• send_feedbackA

  Shakespeare's MonologuesA

  Send feedback about this Shakespeare monologues server: a monologue, play or capability you needed that its tools could not provide, a problem with a result, or praise. Only for feedback about these tools, not about other tasks. Do not include personal information about the user.

  ConnectorNo auth

• fetch-actor-detailsA

  YouTube Transcripts, Comments & Channel AnalyticsA

  Get detailed information about an Actor by its ID or full name (format: "username/name", e.g., "apify/rag-web-browser"). Requires the exact ID or full name — do not construct a plausible-looking name and call this tool with it. Use 'output' parameter with boolean flags to control returned information: - Default: All fields true except mcpTools - Selective: Set desired fields to true (e.g., output: { inputSchema: true }) - Common patterns: inputSchema only, description + readme, mcpTools for MCP Actors The 'readme' field returns the summary when available, full README otherwise. Use when querying Actor details, documentation, input requirements, or MCP tools. EXAMPLES: - What does apify/web-fetch do? - What is the input schema for apify/web-scraper? - What tools does this MCP server Actor provide?

  ConnectorOAuth

• fetch-actor-detailsA

  TikTok Transcripts, Comments, Video Breakdown & Shot AnalysisA

  Get detailed information about an Actor by its ID or full name (format: "username/name", e.g., "apify/rag-web-browser"). Requires the exact ID or full name — do not construct a plausible-looking name and call this tool with it. Use 'output' parameter with boolean flags to control returned information: - Default: All fields true except mcpTools - Selective: Set desired fields to true (e.g., output: { inputSchema: true }) - Common patterns: inputSchema only, description + readme, mcpTools for MCP Actors The 'readme' field returns the summary when available, full README otherwise. Use when querying Actor details, documentation, input requirements, or MCP tools. EXAMPLES: - What does apify/web-fetch do? - What is the input schema for apify/web-scraper? - What tools does this MCP server Actor provide?

  ConnectorOAuth

• fetch-actor-detailsA

  Meta Ad Library, Google Ads Transparency & Video Ad AnalyzerA

  Get detailed information about an Actor by its ID or full name (format: "username/name", e.g., "apify/rag-web-browser"). Requires the exact ID or full name — do not construct a plausible-looking name and call this tool with it. Use 'output' parameter with boolean flags to control returned information: - Default: All fields true except mcpTools - Selective: Set desired fields to true (e.g., output: { inputSchema: true }) - Common patterns: inputSchema only, description + readme, mcpTools for MCP Actors The 'readme' field returns the summary when available, full README otherwise. Use when querying Actor details, documentation, input requirements, or MCP tools. EXAMPLES: - What does apify/web-fetch do? - What is the input schema for apify/web-scraper? - What tools does this MCP server Actor provide?

  ConnectorOAuth