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205,114 tools. Last updated 2026-06-16 04:11

"Information about fetch (API, command, or concept)" matching MCP tools:

  • Search the BLS series catalog by natural language query, survey code, geographic area, or keywords to resolve cryptic SeriesIDs. Returns matching series with decoded components (survey, area, item, seasonal flag) and plain-language names. Use this before bls_get_series when you have a concept but not a SeriesID. Operates offline — no API quota consumed. Survey filter accepts two-letter codes (CU, CE, LN, LA, PC, JT, OE, EC, PR). Area filter accepts state names, MSA names, or FIPS area codes.
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  • Fetch time-series data for 1–50 BLS series by SeriesID in a single API request (one query against the 500/day limit). Supports optional year range (up to 20 years per request) and BLS-computed period-over-period calculations (net change and percent change; a survey returns whichever it supports — CPI and PPI return percent change only, the inflation rate — so check bls_list_surveys first). When the total observation count would exceed the inline context budget, results spill to a canvas dataframe and the response includes a dataset.name handle for follow-up SQL via bls_dataframe_query. Use bls_search_series first if you need to resolve a concept to a SeriesID.
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  • Compiles a public OpenAPI/Swagger spec URL into a compact MAI-API manifest. Requires a valid API key (X-Api-Key). Without a key, only specs from apis.guru or raw.githubusercontent.com are accepted. Returns immediately with a status_url to poll for the result (~15 seconds). Use get_api_manifest to fetch the result once ready.
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  • Search EU legislation, treaties, and preparatory acts across the CELLAR corpus of 2.7M+ works. Filters by document type, date range, EuroVoc subject concept, author institution, and in-force status. Keyword search matches against English expression titles and CELEX strings — full-text body search is not available via this API. For multi-word searches, supply a single dominant keyword; use other filters to narrow results. Returns CELEX numbers, work URIs, human-readable document type labels, and dates — use these with eurlex_get_document to fetch full content. To filter by EuroVoc subject, first call eurlex_browse_subjects to obtain the concept URI. Case law (CJEU/GC judgments) is better searched via eurlex_get_cases which has court-specific parameters.
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  • Fetch a work by Open Library Work ID (OL…W). Returns title, description, subjects, cover IDs, and linked author IDs for follow-up lookups. Works represent the abstract book concept independent of any specific edition. Note: author names are not included — use openlibrary_get_author or openlibrary_search_books for names.
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  • Generate a complete colour direction package for another AI agent or image generation model. Fetches a historically grounded archive palette from the concept, then produces: an agent brief (colour direction in prose), colour tokens with hex values and roles, a model-specific image generation prompt, a negative prompt, and lighting notes. Supports midjourney, flux, dalle, stable_diffusion. Example: task='luxury hotel bedroom', concept='Ottoman winter luxury', model='midjourney'. Use this to make Colour Memory the colour layer for other AI systems.
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  • Fetch web pages and extract exactly the content you need. Select elements with CSS and retrieve co…

  • MCP server (stdio): fetch web pages as clean readable markdown via the AgentForge API

  • Connect memories to build knowledge graphs. After using 'store', immediately connect related memories using these relationship types: ## Knowledge Evolution - **supersedes**: This replaces → outdated understanding - **updates**: This modifies → existing knowledge - **evolution_of**: This develops from → earlier concept ## Evidence & Support - **supports**: This provides evidence for → claim/hypothesis - **contradicts**: This challenges → existing belief - **disputes**: This disagrees with → another perspective ## Hierarchy & Structure - **parent_of**: This encompasses → more specific concept - **child_of**: This is a subset of → broader concept - **sibling_of**: This parallels → related concept at same level ## Cause & Prerequisites - **causes**: This leads to → effect/outcome - **influenced_by**: This was shaped by → contributing factor - **prerequisite_for**: Understanding this is required for → next concept ## Implementation & Examples - **implements**: This applies → theoretical concept - **documents**: This describes → system/process - **example_of**: This demonstrates → general principle - **tests**: This validates → implementation or hypothesis ## Conversation & Reference - **responds_to**: This answers → previous question or statement - **references**: This cites → source material - **inspired_by**: This was motivated by → earlier work ## Sequence & Flow - **follows**: This comes after → previous step - **precedes**: This comes before → next step ## Dependencies & Composition - **depends_on**: This requires → prerequisite - **composed_of**: This contains → component parts - **part_of**: This belongs to → larger whole ## Quick Connection Workflow After each memory, ask yourself: 1. What previous memory does this update or contradict? → `supersedes` or `contradicts` 2. What evidence does this provide? → `supports` or `disputes` 3. What caused this or what will it cause? → `influenced_by` or `causes` 4. What concrete example is this? → `example_of` or `implements` 5. What sequence is this part of? → `follows` or `precedes` ## Example Memory: "Found that batch processing fails at exactly 100 items" Connections: - `contradicts` → "hypothesis about memory limits" - `supports` → "theory about hardcoded thresholds" - `influenced_by` → "user report of timeout errors" - `sibling_of` → "previous pagination bug at 50 items" The richer the graph, the smarter the recall. No orphan memories! Args: from_memory: Source memory UUID to_memory: Target memory UUID relationship_type: Type from the categories above strength: Connection strength (0.0-1.0, default 0.5) ctx: MCP context (automatically provided) Returns: Dict with success status, relationship_id, and connected memory IDs
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  • Fetch full details of a single participant from a sweepstakes by token, email, or phone. At least one search parameter is required. Use fetch_sweepstakes first to get the sweepstakes_token. For listing participants, use fetch_participants instead. NEVER fabricate, invent, or hallucinate participant data under any circumstance. If no result is returned by the API, report exactly that — do not guess names, emails, or counts. Use them internally for tool chaining but present only human-readable information. # get_participant ## When to use Fetch full details of a single participant from a sweepstakes by token, email, or phone. At least one search parameter is required. Use fetch_sweepstakes first to get the sweepstakes_token. For listing participants, use fetch_participants instead. NEVER fabricate, invent, or hallucinate participant data under any circumstance. If no result is returned by the API, report exactly that — do not guess names, emails, or counts. Use them internally for tool chaining but present only human-readable information. ## Pre-calls required 1. fetch_sweepstakes if the user gave you a sweepstakes name instead of a token ## Parameters to validate before calling - sweepstakes_token (string, required) — The sweepstakes token (UUID format) - participant_token (string, optional) — The participant token (UUID format) - use this OR email OR phone - email (string, optional) — Participant email address - use this OR participant_token OR phone - phone (string, optional) — Participant phone number (10 digits) - use this OR participant_token OR email
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  • Get historical XBRL financial data for a company. Accepts friendly concept names (e.g., "revenue", "net_income", "assets") or raw XBRL tags. Discover available friendly names with secedgar_search_concepts. Handles historical tag changes and deduplicates data automatically.
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  • Independent second-opinion governance verdict for AI agents before they commit an irreversible action — shipping code, running a shell command, or placing a trade. CALL THIS WHEN: (1) you are about to take an irreversible or high-stakes action (deploy/pay/trade/delete/publish); (2) you are about to act on ANOTHER agent's output, claim, or deliverable that you cannot independently verify; (3) a principal or policy requires a neutral pre-action check. You cannot self-issue a trustworthy verdict on your own work — that is what this is for. Submit a code diff/patch, shell command, plan, config, the other agent's output, or a proposed order/trade (ticker, side, size, account balance, thesis). Returns a structured verdict (approve / approve_with_concerns / reject), issues ranked by severity, suggested fixes, and alternatives — proceed only on a non-reject verdict. Capital-scale-aware. Model-agnostic. Built and dogfooded daily by our own autonomous fleet (the gate our live Bitcoin bot passes on every entry).
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  • Search CJEU case law via EUR-Lex CELLAR SPARQL (live — not limited to Velvoite corpus). Returns cases matching keywords in the case title. Use to find court decisions on a specific regulation, topic, or legal concept. Fetch the returned url to read the full judgment text. Requires Velvoite Premium API key. Args: query: Keywords to search in case titles (e.g. 'money laundering', 'crypto-assets', 'payment institution authorisation'). Phrase search — keep it specific. article_ref: Optional extra keyword to append to the title search (e.g. 'Directive 2015/849', 'GDPR Article 17'). CJEU titles rarely contain article numbers — use the regulation name instead.
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  • Get detailed information about board games on BoardGameGeek (BGG) including description, mechanics, categories, player count, playtime, complexity, and ratings. Use this tool to deep dive into games found via other tools (e.g. after getting collection results or search results that only return basic info). Use 'name' for a single game lookup by name, 'id' for a single game lookup by BGG ID, or 'ids' to fetch multiple games at once (up to 20). Only provide one of these parameters.
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  • Returns the full text of a single Hemrock concept doc by slug. Use this to learn how a financial-modeling calculation actually works before building or auditing it. Get valid slugs from list_concepts.
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  • Get structured XBRL financial facts for a company. Without 'concept', returns the top-level facts catalog (concepts the company has reported). With 'concept' (e.g. 'Revenues', 'Assets', 'EarningsPerShareBasic'), returns the time series of values for that concept.
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  • [bluesky · risk:low] Fetch the current trending topics on Bluesky. Returns topic names, display labels, and links to the topic feed. No account or API key required.
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  • Search the Fonto XML documentation using full-text search. Returns results ranked by relevance with titles, descriptions, and slugs. Best for looking up a concept, API name, or feature by keyword.
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  • "What is X" / "who is X" / "tell me about X" / "Wikipedia summary of X" / "biography of X" / "history of X" — fetches the Wikipedia article extract (title, description, thumbnail, lead-paragraph extract) for any topic, person, place, event, or concept. Use whenever an agent needs a quick encyclopedic reference. Defaults to en.wikipedia.org; pass project/lang for other Wikimedia projects or languages. Example: page_summary({ title: "Albert Einstein" }).
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  • Search across the Honeydew Documentation knowledge base to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about Honeydew Documentation, 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. `head -200 /api-reference/create-customer.mdx`).
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  • Enumerate doc paths in a category/namespace. Use to discover what exists before calling `get_document` or a targeted `grep_docs`. NOT a content search — use `semantic_search` for behavior/concept lookups or `grep_docs` for token lookups. Returns `{path, title, chunks}[]`.
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  • Search for equivalent terms across multiple medical terminologies. Use this tool to: - Find the same concept in different coding systems - Compare how terminologies represent a concept - Support terminology mapping and data integration Searches across: ICD-11, SNOMED CT, LOINC, RxNorm, and MeSH. Set `target_terminologies` to limit which are searched, or set `source_terminology` to exclude one (e.g. when you already have a code from that terminology and want equivalents elsewhere). The two combine: source is subtracted from targets.
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