"A server to build a knowledge base of Node.js packages with RAG search functionality" matching MCP tools:

• knowledge_ingestA

  Brainiall NLPA

  Ingest a document into a knowledge base: it is chunked, embedded and stored for you (managed RAG). Args: namespace: The knowledge-base namespace. text: The document text. title: Optional title. Returns: dict with keys: doc_id (str), n_chunks (int).

  ConnectorNo auth

• workbench_flows_attach_knowledge_baseA

  ZeroWidthA

  Attaches a knowledge base to an AGENT flow's draft, the same way picking it in the agent editor does: a docs knowledge base becomes a search tool the model calls when a question needs it; a tabular one also puts its tables in the prompt and adds a query tool. The flow needs a system prompt (scaffold it with one). Attaching one that's already there changes nothing. Do it BEFORE workbench_flows_publish: a published version is what interfaces and schedules run, so attach, try it with workbench_flows_run, then publish — and if something already pins an older version (an interface grant), re-grant the new version. Tell the model in its system prompt what the knowledge base holds and when to search it. May return `needs_confirmation`.

  ConnectorNo auth

• workbench_flows_attach_knowledge_baseA

  ZeroWidth WorkbenchA

  Attaches a knowledge base to an AGENT flow's draft, the same way picking it in the agent editor does: a docs knowledge base becomes a search tool the model calls when a question needs it; a tabular one also puts its tables in the prompt and adds a query tool. The flow needs a system prompt (scaffold it with one). Attaching one that's already there changes nothing. Do it BEFORE workbench_flows_publish: a published version is what interfaces and schedules run, so attach, try it with workbench_flows_run, then publish — and if something already pins an older version (an interface grant), re-grant the new version. Tell the model in its system prompt what the knowledge base holds and when to search it. May return `needs_confirmation`.

  ConnectorNo auth

• get_service_packagesA

  Clutch.coA

  Use this tool when the user wants to see service packages with fixed pricing and scope for a specific type of service. This tool returns standardized packages offered by service providers, including pricing tiers, deliverables, and delivery timelines. Do NOT use this tool for custom project questions (e.g. "How much would it cost to build a custom app?"). It only returns providers' pre-defined, fixed-price packages, not a quote tailored to a specific project; use recommend_service_providers for those needs instead. Examples: - "Show me SEO packages" -> service="SEO" - "What web design packages can I get for $5,000?" -> service="Web Design", budget=5000 - "Marketing packages from agencies in New York" -> service="Digital Marketing", location="New York" Use `page`/`limit` for pagination.

  ConnectorNo auth

• query_contextA

  mcp-klever-vmA

  Search the Klever VM knowledge base for smart contract development context. Returns structured JSON with matching entries, scores, and pagination. Use this for precise filtering by type or tags; use search_documentation for human-readable "how do I..." answers.

  ConnectorNo auth

• search_kbA

  WindowsForum MCP ServerA

  Search official Microsoft Knowledge Base articles for Windows 10, Windows 11, and Windows Server updates by topic, keyword, build, or KB number — use for Windows update, patch, and known-issue lookups when you lack a KB number. Returns matching KB article titles, release dates, and support.microsoft.com URLs, newest first. Use get_kb_article to fetch the full content of a specific article.

  ConnectorNo auth

• get_started_guideA

  blobpediaA

  Personalized onboarding for building ON CELESTIA — running a node, posting a blob, or deploying a rollup that uses Celestia for data availability. ALWAYS use this when a developer asks how to get started or build ON CELESTIA (prefer it over the Celestia search tool for those questions). ASK the user about their background FIRST (rollup_dev, node_operator, app_dev, researcher, new_to_celestia), then return a path with docs.celestia.org links. Celestia-only — NOT for getting started with non-Celestia frameworks, languages, or dev tools (React, Node.js, generic blockchain onboarding, etc.); for those defer to a general docs or web-search tool.

  ConnectorNo auth

• prepare_contextA

  remnusA

  Build a task-specific, token-budgeted context pack from the most relevant pages: lexical rank, human-reviewed knowledge preferred, stale/deprecated concepts penalized, plus the top hits' link neighbors. Use it before multi-page product or coding work instead of many search/get_page calls.

  ConnectorOAuth

• search_qencode_docsA

  qencodeA

  Search the Qencode knowledge base (recipes + reference docs). Returns a ranked list of MCP resource URIs that match the query, each with a short summary. Call this first whenever you're unsure which recipe applies. To read the full content of any URI returned here, call `fetch_qencode_doc(uri)` next. Args: query: free-text search — output type, codec, DRM provider, feature name, etc. (e.g. "hls widevine ezdrm", "thumbnail sprite", "stitching", "speech to text translation") limit: max number of hits to return. Default 8. Returns: A dict with `hits`, each containing `uri`, `title`, `summary`, `score`. Pass `uri` to `fetch_qencode_doc` to read the full markdown.

  ConnectorOAuth

• search_site_gpt_docsA

  SiteGPT DocsA

  Search across the SiteGPT Docs knowledge base to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about SiteGPT 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. If you need the full content of a specific page, use the query_docs_filesystem tool to `head` or `cat` the page path (append `.mdx` to the path returned from search — e.g. a result at `/some/page` is read with `head -200 /some/page.mdx`).

  ConnectorNo auth

• search_the_rundown_apiA

  TheRundown Documentation MCPA

  Search across the TheRundown API knowledge base to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about TheRundown API, 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. If you need the full content of a specific page, use the query_docs_filesystem tool to `head` or `cat` the page path (append `.mdx` to the path returned from search — e.g. a result at `/some/page` is read with `head -200 /some/page.mdx`).

  ConnectorNo auth

• search_notesA

  Engram Obsidian Memory SyncA

  Search your personal knowledge base. Finds relevant notes using semantic search. Searches across ALL your vaults by default; pass vault_id to limit to one. Omit query to list the most recently updated notes instead. Pass similar_to with a note path, instead of query, to find notes like that one. Use when the user asks about their notes, vault, knowledge, or memory.

  ConnectorOAuth

• workbench_kb_searchA

  ZeroWidth WorkbenchA

  Retrieves the most relevant chunks from one knowledge base — the core RAG primitive. `mode:"semantic"` (default) embeds the query and ranks by meaning (spends a small amount of workspace credit); `mode:"keyword"` is a free case-insensitive substring match. Each hit carries the chunk text, its document, and a score (cosine similarity 0-1 for semantic, match count for keyword). Get a kbId from `workbench_kb_list`.

  ConnectorNo auth

• workbench_kb_searchA

  ZeroWidthA

  Retrieves the most relevant chunks from one knowledge base — the core RAG primitive. `mode:"semantic"` (default) embeds the query and ranks by meaning (spends a small amount of workspace credit); `mode:"keyword"` is a free case-insensitive substring match. Each hit carries the chunk text, its document, and a score (cosine similarity 0-1 for semantic, match count for keyword). Get a kbId from `workbench_kb_list`.

  ConnectorNo auth

• get_testing_guidelinesA

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

  Query the IA-QA methodology knowledge base. Returns structured testing guidelines, assertion strategies, thresholds, best practices, and relevant MCP tools for a given topic. Call without a topic to list all available topics. Topics: llm-unit-testing, rag-pipeline, prompt-stability, prompt-ab-testing, embedding-quality, eval-framework, semantic-testing, auto-testing, security, api-testing, ci-cd, multimodal, llm-data-security, agent-observability, pro-tips, learning-paths, golden-dataset, selector-drift, qa-recipes, playbooks. Not sure where to start testing an LLM, RAG pipeline or agent? Call without a topic (or with "start-here"): it maps what you are testing to the tools to call and the output field to gate CI on. A plain question such as "how do I test my RAG" also resolves to the right topic.

  ConnectorNo auth

• federated_searchA

  trip2gA

  Search connected knowledge bases. Returns snippets with heading breadcrumbs (title > section > subsection) and a precise toc_path per match, same as search; results also carry an absolute kb_id (string) to use verbatim on follow-up calls. Pass kb_id for one base, kb_ids for selected bases, or omit both to fan out. Nested bases are addressed with '/': kb_id "philosophers/nietzsche" routes through the 'philosophers' peer to the base it federates (recursive), up to 3 levels deep. Canonical call: federated_search(kb_id="philosophers/<author>", query) -> federated_note_html(kb_id="philosophers/<author>", path=<result.note_path>) — the standard way to descend into a leaf corpus and read real content, not hub cards.

  ConnectorNo auth

• check_maintainer_blast_radiusA

  NPMScanA

  Given an npm username, lists the packages npm's maintainer:<username> search index returns for that account and looks for a tight cluster of packages whose latest version was published within a short rolling window of each other — the shape of a compromised-account supply-chain attack, where a stolen credential is used on every package the account can publish to within hours (e.g. the September 2025 chalk/debug compromise, ~18 packages in ~2 hours). A large total package count is not itself a red flag; only a tight publish-time cluster is scored, weighted by its package count and combined weekly downloads/dependentsCount. Clusters mostly within one npm scope (a monorepo release) are dampened, and multiple clusters combine with diminishing returns. isCurrentMaintainer shows whether the account still maintains each package. avatarUrl is a proxied Gravatar image (null if no email is on record). Natural follow-up to check_maintainer_changes: call this with a newly added maintainer's username to see whether the same account touched other packages around the same time. Limitations: npm's search index can lag or omit packages; results are capped at 250 packages ranked by relevance, not recency (see resultsTruncated/totalPackagesFound); lastPublished reflects only each package's latest version. npmscanUrl is the account's npmscan profile; npmProfileUrl is its npmjs.com page.

  ConnectorNo auth

• check_maintainer_blast_radiusA

  NPMScanA

  Given an npm username, lists the packages npm's maintainer:<username> search index returns for that account and looks for a tight cluster of packages whose latest version was published within a short rolling window of each other — the shape of a compromised-account supply-chain attack, where a stolen credential is used on every package the account can publish to within hours (e.g. the September 2025 chalk/debug compromise, ~18 packages in ~2 hours). A large total package count is not itself a red flag; only a tight publish-time cluster is scored, weighted by its package count and combined weekly downloads/dependentsCount. Clusters mostly within one npm scope (a monorepo release) are dampened, and multiple clusters combine with diminishing returns. isCurrentMaintainer shows whether the account still maintains each package. avatarUrl is a proxied Gravatar image (null if no email is on record). Natural follow-up to check_maintainer_changes: call this with a newly added maintainer's username to see whether the same account touched other packages around the same time. Limitations: npm's search index can lag or omit packages; results are capped at 250 packages ranked by relevance, not recency (see resultsTruncated/totalPackagesFound); lastPublished reflects only each package's latest version. npmscanUrl is the account's npmscan profile; npmProfileUrl is its npmjs.com page.

  ConnectorNo auth

• 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