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569,407 tools. Updated 2026-09-14 23:27

"mcp server fetch" matching MCP tools:

  • Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call it; `resource:{uri}` returns the resource's live data (core resources resolved server-side — also the bridge for clients without MCP resource support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's latest combined research signal. Triggers: ChatGPT connectors / Deep Research call this after `search`. Clients without MCP resource support can call it directly with a known resource id, e.g. fetch("resource:market://global/summary"). When to call: whenever the full content behind a search result id is needed. Prerequisites: a valid id — from `search` results or a known namespace id. Next steps: for tool docs, call the named tool via tools/call; for signals, get_signal_detail / explain_decision for deeper evidence. Caveats: uncovered resource uris return description-only text (no fabricated data). `text` is a JSON document for resource/signal ids. Output: {id, title, text, url, metadata, disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Args: id: document id — "tool:{name}", "resource:{uri}", or "signal:{market}:{symbol}" (market: crypto / kr_stock / us_stock) Disclaimer: Information only, not investment advice.
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  • Get Lenny Zeltser's CTI cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `cti_load_context`. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • Connectivity check — returns server version and current timestamp. Use to verify MCP server is reachable before calling other tools.
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  • Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."
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  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
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  • WHAT: Fetch one public discovery file from www and return a line window. REQUIRED which. IDs (aliases folded): llms, llms-full, llms-index, llms-keywords, llms-serp, llms-impressum-kontakt, llms-orte-geo, llms-urheberrecht, llms-copyright, llms-mcp-server, llms-mcp-web, robots, sitemap-txt, sitemap-xml, ai-txt, ai-plugin, answer-engine, ard, ai-catalog, auth-md, mcp-readme, agent-skills. summary = the line window (this is the file body). Use offset/limit + nextOffset to page. Byte caps apply (keywords huge). Unknown which → unknown_discovery. Prefer dedicated get_llms_txt / get_sitemap_txt / get_llms_mcp_server when you know the file. Policy files say ai-train=no.
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Matching MCP Servers

  • A
    license
    A
    quality
    C
    maintenance
    An MCP server that enables AI assistants to fetch web content in multiple formats (HTML, JSON, text, Markdown) with intelligent content extraction, chunk management, and browser automation support.
    5
    44 npm
    15
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    An MCP server that fetches web content and converts it to clean markdown using the Defuddle library, enabling LLMs to read web pages with better extraction than the default fetch server.
    32 npm
    5
    MIT

Matching MCP Connectors

  • Search Luogu problems, fetch statements, explore problem sets and get practice recommendations.

  • MCP server for the PDFGate API. Generate PDFs, manage documents and handle e-signatures.

  • [ChatGPT Connector compat] Fetch memory by ID. Exists to satisfy ChatGPT Deep Research's required `search`/`fetch` tool contract. Native MCP clients should fetch via `recall` + memory_id, or use the API's GET /memories/{id} endpoint directly. Returns a single memory with citation support (id, title, url, text fields). Args: id: Memory UUID to fetch ctx: MCP context Returns: Dict with id, title, url, text, metadata fields
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  • Health check: confirm the eDiscovery Decoder News/Calc MCP server is reachable before a demo or when troubleshooting a connection. Returns server name and version. No inputs.
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  • Search Quantustik for S&P 500 tickers by symbol or company name. Paired with fetch — this is the two-tool "search"/"fetch" convention ChatGPT connectors and deep-research clients expect from an MCP server: call search first to get lightweight hits, then fetch(id) on the one(s) worth reading in full. Args: query: Ticker symbol (e.g. "NVDA") or company-name substring (e.g. "nvidia", "apple"). Case-insensitive. Returns a dict with a `results` list of up to 10 {id, title, url} objects — id is the ticker symbol, ranked exact-symbol match first, then company-name/ticker prefix, then substring. Empty query or no scan data returns an empty list, never an error.
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  • Free, no key required. Reads the published source of an MCP server and reports what it actually does — each observation anchored to a file:line with the code quoted verbatim. **Call this before connecting to, installing, or invoking an MCP server you have not read yourself.** Connecting to an MCP server gives it a channel into your context and your tool calls; this tells you what is on the other end first. Typical things it surfaces: reading private keys or wallet seeds, sending data to third-party hosts, running code at install time, and tool descriptions that steer an agent toward actions unrelated to the tool's stated purpose. Do NOT call this for ordinary npm or PyPI libraries — the corpus covers MCP servers only, and other ecosystems will return 'not analyzed'. This reports observations, not a safety verdict. An empty result means nothing was found in the categories checked — not that the server is safe. Corpus: 3,281 MCP servers from the official registry, read at source level. Coverage index (free, no key, findings not included): GET https://sri-test.biz/v1/corpus
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  • Get Lenny Zeltser's IR cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `ir_load_context`. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
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  • Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • Pre-flight security verdict for an MCP server invocation. Judges BOTH server-level reputation AND the server's dependency graph (npm/pypi) against the DugganUSA threat-intel corpus (1.13M+ IOCs, Shai-Hulud + typosquat + LOLBin families). Returns BLOCK / ADVISORY / REVIEW / ALLOW with severity, evidence, dep-graph summary, and HMAC-signed response. REVIEW means we hold NO RECORD of this server -- not that it is safe. Treat REVIEW as do-not-proceed-blindly: a brand-new attacker-published server looks exactly like this. ALLOW is only returned when we actually resolved the server and scanned its dependency graph; check known_to_us and dep_graph.scanned to confirm. Use this BEFORE invoking any other MCP server tool, especially ones installed from outside the official MCP Registry.
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  • Fetch the complete record for ONE MCP server in the agentage directory by its canonical slug: full description, categories, the packages and remote endpoints it ships, the tools it exposes, a ready-to-run install command, and a README excerpt. Use this after mcp_search to get the depth a result card omits - pass a slug exactly as returned by mcp_search. Slugs are canonical and registry-derived ("io-github-github-github-mcp-server"), NOT the plain product name ("github"); if you pass a plain name anyway it is resolved by search as a fallback - a single confident match returns that server (with `resolved_from` set), anything else returns an error naming the candidate slugs to retry with. No slug yet? call mcp_search first. Read-only.
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  • Check any public URL RIGHT NOW: is it up, HTTP status, response time in ms. With kind:"mcp" it instead performs a real JSON-RPC initialize handshake against a streamable-HTTP MCP server endpoint and reports the server’s self-declared name/version/protocol — useful to tell "the MCP server is down" from "my client is misconfigured". Works without an API key (rate limit 30/hour per IP). For continuous monitoring with alerts, use create_monitor.
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  • Upload a file to the Compoid MCP server. Accepts a data URI (data:<mime>;base64,<data>). Returns the server-side path to use as file_upload in Compoid_create_record or Compoid_update_record.
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  • Clear the current auth token locally. Does NOT revoke server-side MCP tokens — revoke from the Neuron dashboard (Settings > MCP Tokens) for full invalidation.
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  • Read or search messages in one chat: browse latest, search text, fetch by ids, or load replies to a message (comments, forum topics, threads). Use from_user to filter by sender (server-side, per-chat only). Use context to include neighboring messages and reply chains around each result. Use include_replies to fetch up to 5 direct replies per result. Do not combine message_ids with query or reply_to_id. Success: messages, has_more, optional total_count and discussion fields. Full documentation: https://github.com/alexeyleshchenko/fast-mcp-telegram/blob/main/docs/Tools-Reference.md
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  • Read or search messages in one chat: browse latest, search text, fetch by ids, or load replies to a message (comments, forum topics, threads). Use from_user to filter by sender (server-side, per-chat only). Use context to include neighboring messages and reply chains around each result. Use include_replies to fetch up to 5 direct replies per result. Do not combine message_ids with query or reply_to_id. Success: messages, has_more, optional total_count and discussion fields. Full documentation: https://github.com/alexeyleshchenko/fast-mcp-telegram/blob/main/docs/Tools-Reference.md
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  • Measure a public MCP endpoint against five conditions: it speaks MCP, it publishes an A2A agent card, it declares who pays it, identical input returns identical output, and the verdict itself can be recomputed by anyone. Free, no key. Conformance and disclosure only; this says nothing about whether any figure the checked server returns is correct. By default no tool on the checked server is called, so determinism comes back as not measured rather than guessed. Set allow_tool_call true only for a server you control.
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