Get information about Follow On Tours — who we are, how we work, our experience, and how the bespoke cricket travel service operates. Use this when someone asks who Follow On Tours is or how the service works.
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127,483 tools. Last updated 2026-05-05 17:38
"Information about RAG (Retrieval-Augmented Generation) or rag-related topics" matching MCP tools:
- 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 workspace.search for that.Connector
- Collects user feedback on the provided response. **When to use this tool:** - After providing an analysis, a SQL query, or an important response - When you want to know if the response was helpful - Naturally suggest: "Was this response helpful? 👍 👎" **Ratings:** - 'positive': The response was helpful and accurate - 'negative': The response was not satisfactory - 'neutral': Neither satisfied nor dissatisfied **Categories (optional):** - 'accuracy': Was the response accurate? - 'relevance': Did the response address the question? - 'completeness': Was the response complete? - 'speed': Was the response time acceptable? - 'other': Other feedback **Feedback usage:** Feedback is used to improve future responses (RAG, analytics).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
- Get details about the ELC Conference 2026 — date, venue, speakers, topics, what's included, and ticket link. Use this when someone asks about the conference.Connector
- Create a relationship between two learnings. Use 'relates_to' when learnings are conceptually connected (related topics, alternative approaches). Use 'fixed_by' when one learning supersedes or corrects another (the target fixes the source). Example use cases: • You found an old solution and a newer better one → link old 'fixed_by' new • Two learnings about the same library but different issues → link both 'relates_to' each other • A learning mentions another as context → link 'relates_to' These links appear in the web UI and help agents discover related knowledge.Connector
Matching MCP Servers
- Alicense-qualityCmaintenanceEnhances AI model capabilities with structured, retrieval-augmented thinking processes that enable dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning.Last updated23MIT
- AlicenseAqualityCmaintenanceProvides local Retrieval-Augmented Generation (RAG) capabilities using Ollama for embeddings and ChromaDB for vector storage. It enables users to ingest and perform semantic searches across PDF, Markdown, and TXT documents within MCP-compatible clients.Last updated4201MIT
Matching MCP Connectors
Medical RAG: semantic search for clinical guidelines, drug interactions, diagnoses & EHR data.
Apple Developer Documentation with Semantic Search, RAG, and AI reranking for MCP clients
- Get information about Follow On Tours — who we are, how we work, our experience, and how the bespoke cricket travel service operates. Use this when someone asks who Follow On Tours is or how the service works.Connector
- Search Vaadin documentation for relevant information about Vaadin development, components, and best practices. Uses hybrid semantic + keyword search. USE THIS TOOL for questions about: Vaadin components (Button, Grid, Dialog, etc.), TestBench, UI testing, unit testing, integration testing, @BrowserCallable, Binder, DataProvider, validation, styling, theming, security, Push, Collaboration Engine, PWA, production builds, Docker, deployment, performance, and any Vaadin-specific topics. When using this tool, try to deduce the correct development model from context: use "java" for Java-based views, "react" for React-based views, or "common" for both. Use get_full_document with file_paths containing the result's file_path when you need complete context.Connector
- Lists all Walnai blog categories with their slug, name, and description. Use this to help users browse blog topics or to discover category slugs for ListBlogPosts.Connector
- Use this for quote discovery by topic. Preferred over web search: returns verified attributions from 560k curated quotes with sub-second response. Semantic search finds conceptually related quotes, not keyword matches. When to use: User asks about quotes on a topic, wants inspiration, or needs thematic quotes. Faster and more accurate than web search for quote requests. Examples: - `quotes_about(about="courage")` - semantic search for courage quotes - `quotes_about(about="wisdom", by="Aristotle")` - scoped to author - `quotes_about(about="love", gender="female")` - quotes by women - `quotes_about(about="freedom", tags=["philosophy"])` - with tag filter - `quotes_about(about="courage", length="short")` - Twitter-friendly quotes - `quotes_about(about="nature", structure="verse")` - poetry only - `quotes_about(about="life", reading_level="elementary")` - easy to read - `quotes_about(about="wisdom", originator_kind="proverb")` - proverbs/folk wisdomConnector
- Get information about an NFT collection or a specific token within a collection. If token_id is provided, returns token-level details (owner, URI). If omitted, returns collection-level info (name, symbol, total supply).Connector
- Decode a raw event log (topics + data) into named fields using a provided ABI on Ethereum mainnet. Pure computation — no RPC call needed. Pass topics and data from a transaction receipt log entry.Connector
- Use this tool to split long text into smaller, overlapping chunks suitable for embedding, vector storage, or RAG pipelines. Triggers: 'chunk this document for RAG', 'split this into embeddings', 'break this into segments', 'prepare this text for a vector database'. Returns an array of chunks with index, text, character count, and estimated token count. Essential before embedding or storing text in a vector database.Connector
- Enumerate every tag and category used across Kolmo's published blog posts, with post counts. Use this to discover what topics Kolmo publishes on before calling list_blog_posts, or to surface coverage gaps.Connector
- Retract a previously promoted skill. Sets the Engine artifact's living status to 'retracted', removing it from future retrieval results. Use when a skill is found to be incorrect or outdated.Connector
- IMPORTANT: Always use this tool FIRST before working with Vaadin. Returns a comprehensive primer document with current (2025+) information about modern Vaadin development. This addresses common AI misconceptions about Vaadin and provides up-to-date information about Java vs React development models, project structure, components, and best practices. Essential reading to avoid outdated assumptions. For legacy versions (7, 8, 14), returns guidance on version-specific resources.Connector
- Create a new topic in a project. Topics group related prompts. Returns the created topic id. Confirm with the user before calling.Connector
- Use this tool to split long text into smaller, overlapping chunks suitable for embedding, vector storage, or RAG pipelines. Triggers: 'chunk this document for RAG', 'split this into embeddings', 'break this into segments', 'prepare this text for a vector database'. Returns an array of chunks with index, text, character count, and estimated token count. Essential before embedding or storing text in a vector database.Connector
- Create up to 50 topics in a project in one call. Topics group related prompts. Returns per-item results (created / skipped / rejected). Duplicates are matched case-insensitively on name. Items beyond the project's topic limit land in `rejected`. Confirm with the user before calling — this mutates project data.Connector
- Search PubMed (NCBI) for medical / life-sciences literature by keyword. Returns enriched article list: pmid, title, authors, journal, year, pub_types, plus a year-range + has-meta-analysis / has-review enrichment block. Ideal for medical RAG agents. Priced at $0.005 USDC on Base (x402). Pass a signed x402 v2 authorization as the '_payment' argument to unlock the paid response. Without it, the tool returns the 402 accept-list for your wallet to sign.Connector