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744,816 tools. Updated 2026-11-05 00:14

"A server for semantic API information and resources" matching MCP tools:

  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Get information about the organization your agent is linked to. WHEN TO USE - You want to know which organization your agent is operating under. - You need to list the members of your linked org (e.g., to decide which member should review a deliverable). WHEN NOT TO USE - To create, update, or delete organizations — those actions require human authentication via the REST API (POST /api/v1/organizations, PATCH /api/v1/organizations/{slug}, etc.). BEHAVIOR - Read-only. Auth required: agent API key. Rate-limited to 60 req/min. - Returns an error if your agent is not linked to any organization (agents.org_id IS NULL). - action='get_my_org': returns org name, slug, tier, owner, and member count. - action='list_members': returns human_id and role for each member. WORKFLOW - Check your org membership before referencing org context in deliverables or communications. - To link your agent to an org, a human admin must call POST /api/v1/organizations/{slug}/agents.
    ConnectorNo auth
  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Discover content franchises within a domain. Two modes: pass `tag` for a precise taxonomy match (every game tagged 'co-op'), or pass `query` for free-text SEMANTIC search powered by pgvector embeddings — finding franchises by meaning ('dark atmospheric games about isolation') even when no literal tag matches. Results are verifiable: tag mode carries tag confidence/corroboration, semantic mode carries a similarity score; both carry entity freshness. When to use: an agent wants a domain-scoped shortlist by tag or by intent. Inputs: a domain plus either a tag or a free-text query.
    ConnectorNo auth
  • Before security-sensitive tooling or agent operations: find recent threads relevant to a task, with source links, provenance and matching keywords. Keyword overlap on title, tags and excerpt over the last 200 active threads; not semantic search and not the full archive (use search for that). Seeds excluded by default.
    ConnectorNo auth
  • Fetch the full content for one id returned by `search`: a rental listing (rental:<uuid>), a plan set (plan:<uuid>) or a published page (page:<route>). Returns {id, title, text, url, metadata}. Always cite the url. Hosts that can call specific tools should prefer get_rental or the resources.
    ConnectorNo auth

Matching MCP Servers

  • A
    license
    Not graded
    quality
    F
    maintenance
    LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.
    21 npm
    1
    MIT

Matching MCP Connectors

  • Validate emissions data against Open Footprint, check EU CBAM records, query verified methane data

  • Search the FAA handbooks, advisory circulars and Airman Certification Standards (ACS) used for pilot training, and read any page in full with its figures, charts and tables. Every result links back to the exact page so answers can be cited. Free, public, no API key.

  • Create a custom CodePic hand-drawn style diagram by specifying nodes and edges. Requires API Key authentication. Returns a public view URL. **THIS IS THE DEFAULT TOOL FOR ANY USER-DESCRIBED DIAGRAM.** Whenever the user describes a diagram they want ("draw an A/B test flowchart", "帮我画一个登录流程", "a system architecture with a load balancer and 3 servers", etc.), build it here from their description. Do NOT fall back to `create_from_template` / `list_templates` unless the user explicitly asked for a template. When responding to the user, present the returned URL as a clickable markdown link (e.g. `[Open in CodePic →](URL)`) so the user can click it directly in their AI client (Cursor / Claude / etc.). **Container nesting (IMPORTANT — use whenever possible):** - Set `parentId` on a node to nest it inside another node. ANY node type can be a container. - The parent automatically becomes draggable-as-a-group and users can keep dropping elements into it. - Call `get_shape_catalog` with tag `container-capable` to choose among native structural containers and adaptive semantic shapes such as rectangles, circles, ellipses, diamonds, cylinders, and hexagons. - Parent bounds are expanded automatically using the selected shape's title and outline safe area. - Use absolute canvas coordinates for all nodes — child coordinates are auto-converted to parent-relative. - Set node `name`, `description`, and `tags` when later MCP/Agent reads need stable business semantics beyond visible text. - **Rule**: whenever 2+ nodes logically belong to the same module / component / region, create a container node first and set `parentId` on each child. **Design tips for beautiful diagrams:** - Use semantic types: `button-primary` for CTA buttons (auto blue), `diamond` for decisions - Pick a color palette and apply it consistently — light fill + darker stroke of the same hue: • Blue: fillColor #e3f2fd / #bbdefb, strokeColor #1565c0, fontColor #1565c0 (or #ffffff on dark fill) • Green: fillColor #e8f5e9 / #c8e6c9, strokeColor #2e7d32, fontColor #1b5e20 • Purple: fillColor #f3e5f5 / #e1bee7, strokeColor #6a1b9a, fontColor #4a148c • Neutral: fillColor #f8fafc / #f1f5f9, strokeColor #475569, fontColor #1e293b - Each semantic group (decisions, processes, I/O) should share a fill color to create visual hierarchy - Dark fill (e.g. #1565c0, #ef4444) → fontColor #ffffff; light fill → fontColor #111827
    ConnectorNo auth
  • Create a public booking request. Does NOT require an API key, but DOES require: (1) requester identity — fullName plus at least email or phone, (2) submission context — channel and whether an agent assisted, (3) authorization.humanIntentConfirmed must be true. The booking is created as pending_confirmation — use public_booking_confirm with the returned confirmationToken to confirm. A bookingToken is also returned for future lifecycle management (cancel, reschedule). Rate-limited per IP+org. All requests are audited with semantic decision codes. Use public_service_list → public_availability_get_slots → public_booking_create → public_booking_confirm as the complete public booking flow.
    ConnectorNo auth
  • Classify MIME type, charset and bounded content length. Use only for public HTTP(S) resources; it does not execute JavaScript or bypass access controls. Pass url as an absolute public HTTP(S) URL. Keep fresh=false to allow cache reuse; set fresh=true only when a new upstream fetch is required.
    ConnectorNo auth
  • Maps only stable Tier1 finding identifiers to approved Tier1 services and public resources. Call after a Tier1 score or email-domain check. Do not submit prose, URLs, customer information, or invented identifiers. This tool performs no arbitrary fetching, makes no contact request, changes nothing, and stores nothing.
    ConnectorNo auth
  • Return safe network timing, payload and cacheability diagnostics. Use only for public HTTP(S) resources; it does not execute JavaScript or bypass access controls. Pass url as an absolute public HTTP(S) URL. Keep fresh=false to allow cache reuse; set fresh=true only when a new upstream fetch is required.
    ConnectorNo auth
  • Uninstall a release and remove the resources it created, including volume data. Use it, not delete_resource, for anything install_template created. Provide the release `name`.
    Connector
    Destructive
    OAuth
  • Given an exact tag/skill (e.g. 'docker', 'gcp'), returns EVERY entry with that tag, uncapped, grouped by type with a real count per type. Unlike related_entries (capped at 15, requires a starting entry id) or query_knowhow (semantic, ranked, may over- or under-include), this is an EXACT tag match against every entry -- the right tool for 'how many X have I completed/done' or 'do I have any real evidence for X at all'. Tags are exact strings from a prior list_by_type/related_entries/query_knowhow result's tags array -- this is NOT semantic search; a tag never assigned during ingest returns found:false, try query_knowhow instead. Each type's entries sort by captured_at ascending (oldest first); entries with no captured_at are moved to the end and counted in undated_count, never silently sorted as if their date were known.
    ConnectorNo auth
  • Find meters when the exact slug is unknown. The backend searches for a literal, case-insensitive substring in slug, label, group and sourceNote, and orders matches by slug. This is not semantic search; no matches returns an empty meters array. Use list_meters to browse all meters.
    ConnectorNo auth
  • Search Lacuna's ML/AI corpus for papers, research directions, authors, venues, institutions, novel research hypotheses, and research resources (code repositories, datasets, models, and demos linked to papers). For novel ML/AI research ideas, use search_type="hypothesis", then get_hypothesis on promising results. search_type accepts all, cluster, paper, author, institution, venue, hypothesis, or resource. Use paper for literature and get_paper to read a result. Use other sources for biographies, news, and non-research web content. Resources: search_type="resource" searches GitHub repositories, Hugging Face datasets/models, and Zenodo records that Lacuna has linked to at least one paper. To find benchmark or evaluation datasets, use search_type="resource" with resource_kind="dataset" (for example query "image classification benchmark" or a dataset name like "ImageNet"). resource_kind accepts codebase, dataset, model, or demo (one value or a list); provider accepts github, huggingface, or zenodo. Both filters require search_type "resource" or "all" (with either filter set, only resources are returned). Each result has an external `url`, a Lacuna `context_url`, and `linked_paper_count`; call get_resource on its id to list the linked papers (with their relationship to the resource), then get_paper on those papers for reported results and numbers. Resource search does not support date_from/date_to, venue, year sorting, or semantic ranking. ranking_profile accepts: - default / lexical (default): production ranking; relevance-sorted paper searches combine lexical and semantic retrieval when fields is unset. - semantic: conceptual paper retrieval; supported for paper and all. - bm25_title_abstract / bm25: lexical paper matching over those fields. sort accepts relevance (default), year_desc, or year_asc. Semantic ranking cannot use year sorting; constrain recency with date_from/date_to instead. date_from and date_to are inclusive YYYY, YYYY-MM, or YYYY-MM-DD bounds. author_id_or_url constrains a paper search to one author. Pass an author ID or Lacuna author page URL; it requires search_type="paper". fields optionally restricts and weights lexical fields, for example "title^4,abstract". Supported names are title, abstract, summary, concepts, name, top_names, and venue, plus description, topics, provider_key, and paper_titles for resources (a resource's title already includes its description, topics, README text, and linked paper titles). Fields must exist on the selected search_type, weights must be within 0 < weight <= 100, and fields cannot be combined with semantic ranking.
    ConnectorNo auth
  • Semantic search over academic references by title + abstract, across languages. Only references with an abstract (about half) are covered; use search_references for the rest. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query.
    ConnectorNo auth
  • List the API keys and client-credential pairs of an organization. For each key: its ID, name, type, creation, expiry, last use, revocation time, and the resources it can access. For each client-credential pair (an OAuth client that authenticates with the client credentials grant): its client ID, name, creation time, creator, grant types, scopes, and the resources it can access. Key values and client secrets are never returned. Pass a key's ID to RenameApiKey or DeleteApiKey. Those tools do not work on pairs, so manage pairs in GraphOS Studio or with `rover api-key`. Provide the organization ID, which GetMyIdentity returns. Optionally filter keys by status (ACTIVE by default, or ALL, EXPIRED, REVOKED) and type (OPERATOR, SUBGRAPH, VARIANT, GATEWAY, SCIM). The filters do not apply to pairs. The two lists page separately: page keys with first and after, and pairs with pairsFirst and pairsAfter.
    ConnectorNo auth
  • Get setup info for Rudow's client SDKs (Node.js backend, Python backend) — package name, install command, a minimal config/usage snippet, and how to obtain a project ingest API key. Use this to help a user add logging to their own codebase: install the right package for their stack and write the snippet into their code yourself — this tool only returns information, it does not install anything or touch the user's files. It never creates or reveals an ingest API key; the user must generate one manually from the dashboard (see key_instructions in the result) and paste it in themselves.
    ConnectorAPI key
  • Delete ONE AI package resource of a video in one language (eBook, mind map or quiz) — cannot be undone: its content, PDF, images and the published file are removed, also for legacy resources. Same as the dashboard's Remove. Refused while it is still generating (checked before deleting; if that check fails nothing is deleted). Other languages and resources stay. To remove a failed generation card use panda_delete_ai_workflow.
    Connector
    Destructive
    No auth
  • Re-trigger background semantic training for one dataset and return immediately with status and a confirmation message — the build runs asynchronously, so poll get_dataset_status until model_tier reaches 'schema'. Use after schema changes, alias updates, or to force a fresh model build. epochs (default 80, range 5-500) controls training length. An unknown dataset_id fails with not_found; a dataset whose training backend is unavailable fails with semantic_training_unavailable.
    ConnectorNo auth
  • Pin, edit or unpin a resource (a check or a check group) in a status page section. action=create pins exactly one of checkUid or checkGroupUid and returns the resource. action=update edits one (resourceUid required; omitted fields are kept). action=delete unpins it, returning {deleted, identifier}; the check or group itself is untouched. Read a section's resources with get_status_page include=resources. Annotated destructive and non-idempotent because delete is one of its actions. Every action requires the mcp scope (mcp:read tokens are refused) and at least the user role in the organization.
    Connector
    Destructive
    API key