The MCP tool directory.

Unarchives a specified public or private Slack channel that is currently archived, using its channel ID.

Reverses conversation archival.

Unpins a message, identified by its timestamp, from a specified channel if the message is currently pinned there; this operation is destructive.

Updates an existing Slack User Group, which must be specified by an existing `usergroup` ID, with new optional details such as its name, description, handle, or default channels.

Updates the title, join URL, or desktop app join URL for an existing Slack call identified by its ID.

Replaces all members of an existing Slack User Group with a new list of valid user IDs.

Updates a Slack message, identified by `channel` ID and `ts` timestamp, by modifying its `text`, `attachments`, or `blocks`; provide at least one content field, noting `attachments`/`blocks` are replaced if included (`[]` clears them).

Updates metadata or content details for an existing remote file in Slack; this action cannot upload new files or change the fundamental file type.

Uploads a file to Slack, requiring either `content` (for text) or `file` (for binary data), optionally sharing it in specified `channels` or as a reply via `thread_ts`.

Attempt to log in to a website. Navigates to the login URL, finds email/username and password fields, fills them in, and submits the form with click, Enter, and form-submit fallbacks for Clerk and other multi-step auth UIs. Returns a screenshot and reports whether login succeeded, failed, or needs verification. Always ask the user for credentials first — never guess. If the site requires email verification (OTP code), use read_verification_email to automatically fetch the code from Gmail (requires one-time authorize_email_access setup).

Automatically solve CAPTCHAs on the current page using CapSolver AI. Supports Cloudflare Turnstile, reCAPTCHA v2/v3, and hCaptcha. Detects the CAPTCHA type and sitekey automatically, sends it to CapSolver for solving, injects the token, and optionally submits the form. Use this when a CAPTCHA blocks form submission during browser automation.

Retrieve the full text, metadata, and references of one Space Frontiers document. Use when: you have a `source_uri` from a search hit and need the body to quote, summarize, or extract structured facts; or you want to walk the citation graph via `references` and `referenced_by`. Do not use when: you have not yet found the document — call a `spacefrontiers_search_*` tool first to obtain a real `source_uri`. Do not guess DOIs. Returns title, authors, abstract, content (truncated above ~100K chars), references with URIs, and up to 30 `referenced_by` documents you can fetch next. For documents over ~20K tokens prefer `spacefrontiers_search_in_document` to extract only the passages you need. Examples: `https://doi.org/10.1038/s41586-023-06924-6`, `arxiv:2301.00001`, `pmid:38019072`.

Search peer-reviewed papers, books, patents, and Wikipedia in the Space Frontiers `documents` index. Use when: the user asks about scientific concepts, technical methods, prior art, citations, a DOI / ISBN / arXiv ID / PubMed ID, or wants peer-reviewed sources. Do not use when: the question is about news, current events, ongoing discussions, or social sentiment — call `spacefrontiers_search_social` instead. For general web pages or code, use a different MCP server. Examples: "crispr base editing efficiency", "doi:10.1038/s41586-023-06924-6", "isbn:9780262033848", "arxiv:2301.00001", "transformer attention scaling laws". Tips: - Run 2-6 parallel queries with varied phrasings (synonyms, narrower/broader terms). - Pass an empty `query` plus `filter_issns` to browse recent issues of a specific journal. - Use the returned `source_uri` verbatim with `spacefrontiers_fetch_document` for full text.

Find specific passages inside one Space Frontiers document without reading the whole body. Use when: the document is large (size > ~20K tokens shown in `content_size_tokens`) and you only need the parts relevant to a sub-question, e.g. "what error rates does this paper report?" against a 60-page review. Do not use when: you need the entire document to summarize or quote in full — call `spacefrontiers_fetch_document` instead. Do not call this without first obtaining a real URI via search. If no passage matches the query, the full document is returned in `fallback_full_document` so the caller never has to retry with a second tool call.

Search Reddit, Telegram channels, and YouTube transcripts in the Space Frontiers `social` index. Use when: the user asks about news, recent events, announcements, ongoing discussions, community opinions, or anything time-sensitive that wouldn't be in peer-reviewed literature. Do not use when: the question is about settled scientific knowledge, citations, or prior art — call `spacefrontiers_search_documents` instead. For general web search, use a different MCP server. Examples: "openai gpt-5 release date", "site:reddit.com/r/LocalLLaMA quantization", "@telegram_channel breaking news", "kubernetes 1.33 changes discussion". Tips: - Pair an empty `query` with `filter_uri_prefixes` to browse a subreddit or Telegram channel chronologically (combine with `filter_issued_after` for a time window). - For broad topics, also call `spacefrontiers_search_documents` in parallel for grounded sources.

Search special administrative appeal decisions (특별행정심판 목록 조회). Search decisions from Korean special administrative appeal tribunals. Args: tribunal: Tribunal name in Korean. Valid values: 조세심판원, 해양안전심판원, 국민권익위원회, 인사혁신처 소청심사위원회 query: Search keyword (default "*") display: Number of results per page (max 100, default 20) page: Page number (1-based, default 1) oc: Optional OC override (defaults to env var) type: Response format - "JSON" (default), "XML", or "HTML" search: 1=사건명 (case name), 2=본문검색 (full text) sort: Sort order gana: Dictionary search cls: 재결례유형 (decision type classification) date: Reference date (YYYYMMDD) dpa_yd: Decision date range (YYYYMMDD~YYYYMMDD) rsl_yd: Resolution date range (YYYYMMDD~YYYYMMDD) ctx: MCP context (injected automatically) Returns: Special appeal decision list or error Examples: Search 조세심판원 decisions: >>> special_decc_search(tribunal="조세심판원", query="부가가치세")

Retrieve special administrative appeal decision full text (특별행정심판 본문 조회). Args: tribunal: Tribunal name (same values as special_decc_search) id: Decision serial number (재결례일련번호) oc: Optional OC override type: Response format - "JSON" (default), "XML", or "HTML" ctx: MCP context (injected automatically) Returns: Full decision text or error

Returns Naver's spelling correction for a misspelled search query (오타변환).

Exchange an access token for a user's [Profile](/reference/sso/profile). Because this profile is returned in the [Get a Profile and Token endpoint](/reference/sso/profile/get-profile-and-token) your application usually does not need to call this endpoint. It is available for any authentication flows that require an additional endpoint to retrieve a user's profile.

Discover stocks that align with your investment strategy using the FMP Stock Screener API. Filter stocks based on market cap, price, volume, beta, sector, country, and more to identify the best opportunities.

Add a sub-issue to a parent issue in a GitHub repository.

Persist targeting artifacts (keywords/subreddits) and return policy/preview. Prerequisites: - prompt pack must be acknowledged for `session_id` - artifacts should already be saved for best results Typical next step: - approve targeting (done automatically by `run_full_agentic_onboarding` when enabled) Formats: - keywords: list[str] - subreddit_groups: [{'subreddits': ['name1','name2']}]

Submit a bid on an open job posting. The buyer reviews all bids and awards the job via award_job(). Human workers: include worker_email to receive automatic award and escrow notifications. AI agents: poll view_job(job_id) to check bid status — no email needed. Returns: status: "submitted", bid_id, job_id, proposed_xrp, email_on_award.

Validate and persist core onboarding artifacts for a product/session. Prerequisites: - prompt pack must be acknowledged for `session_id` - payloads should match the artifact schemas below Common use: - called by `run_full_agentic_onboarding` - can also be used for staged/recovery runs Expected formats: - market_position: patch object with market position keys - conversion_notes: {'Product Name','Payment Terms/Plans','General Notes'} - funnels: [{'url','description','primary_use_case', optional 'qualification'}]

Retrieves subscription information including limits and usage statistics for API units, workspace quotas, and API key details. This endpoint is free and does not consume any API units. Use doc tool first to get the real input schema.

Generate schema-aware query suggestions with ready-to-run SQL. Great for exploring unfamiliar databases or finding useful queries.

Claim an open leg of a digital task. First agent to bid wins the leg. You will receive the previous leg's result as context when you start. Complete with swarmhaul_complete_digital_leg.

Submit your completed result for a digital leg you were assigned. Your result will be passed to the next leg's agent as context. Triggers reputation update and SOL settlement.

Confirm completion of a delivery leg you were assigned. Notifies the API that you've delivered. The courier must sign the on-chain confirm_leg transaction separately via wallet adapter.

Get real-time agent economy statistics — active packages, swarms, bids, total volume, registered agents.