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206,665 tools. Last updated 2026-06-17 14:51

"A server for finding information about windows" matching MCP tools:

  • Return the description and install snippets for a named tool or server. For tools: the description and the server it belongs to. For servers: local (stdio, via npx) install snippets for every published server, plus remote (HTTP) connection snippets when a hosted endpoint exists — for every supported client, or one client via the client parameter. Call cyanheads_search first to find valid names.
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  • 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.
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  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
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  • Fetch incident history and scheduled maintenance windows for a vendor. Returns full incident timeline — each investigator update, affected components, and resolution. Filter by status to focus on active incidents (use before deploy), resolved history (for postmortem), or upcoming maintenance windows.
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  • Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")
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  • Call when the user asks about timing a decision for a specific date, or wants to pick the best day from a multi-day window. Covers trip dates, launch days, interview/meeting days, publish/send dates, travel, negotiation windows, relationship moments — any "when to X" question where the answer is a date ("should I X on April 23", "best day this month to Y", "下周四怎么样"). Modes: single date, compare up to 5 dates, or scan a range up to 31 days. Returns score (0-100), verdict, per-layer year/month/day breakdown (alerts + dimension signals), element breakdown, adverse alerts. For multi-month windows use `intentions_ask_month`; for hour precision use `intentions_ask_hour`.
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Matching MCP Servers

  • A
    license
    A
    quality
    D
    maintenance
    Exposes Windows system information and control tools including hardware stats, network details, and process monitoring. It enables AI applications to retrieve real-time data about CPU, memory, drives, and active system processes.
    Last updated
    10
    12
    GPL 3.0

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  • Give your AI agent a phone. Place outbound calls to US businesses to ask, book, or confirm.

  • Cloud-hosted MCP server for Epidemic Sound

  • General search tool. This is your FIRST entry point to look up for possible tokens, entities, and addresses related to a query. Do NOT use this tool for prediction markets. For Polymarket names, topics, event slugs, or URLs, use `prediction_market_lookup` instead. Nansen MCP does not support NFTs, however check using this tool if the query relates to a token. Regular tokens and NFTs can have the same name. This tool allows you to: - Check if a (fungible) token exists by name, symbol, or contract address - Search information about a token - Current price in USD - Trading volume - Contract address and chain information - Market cap and supply data when available - Search information about an entity - Find Nansen labels of an address (EOA) or resolve a domain (.eth, .sol)
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  • Get detailed information about a specific job listing/posting by its job listing ID (not application ID). Use this to view the full job posting details including description, salary, skills, and company info. For job application details, use get_application instead.
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  • Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.
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  • Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.
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  • Run forensic windows analysis (AACE RP 29R-03 §3.3, MIP 3.3 Observational / Dynamic / Contemporaneous As-Is) across multiple Primavera P6 XER snapshots and return the full analysis dict. This is the headline forensic tool — it computes per-window completion shifts, per-window slip registers (per-activity slip with critical/non-critical flag), per-window duration growth on critical-path activities, per-window per-party attribution (Owner / Contractor / Concurrent / Force Majeure / Unattributed), and cumulative project drift from baseline. The attribution math satisfies the AACE 29R-03 §4.1 conservation rule (per-party day buckets sum to project drift within ±1 day, no cascade-double- counting). Use this tool for the full multi-window forensic claim. If you already have a windows result and only want the per-window × per-party grid view, call ``concurrent_delay_matrix`` instead. Args: schedules: list of dicts in chronological order. Minimum 2 entries (baseline + at least one update). Each dict must contain ``label`` (str) and EXACTLY ONE of: - ``xer_path`` — server-side filesystem path, OR - ``xer_content`` — full XER text content. Use ``xer_content`` when calling a hosted MCP server from a remote client whose XER lives locally. project_name: optional override; auto-picked from XER if "". baseline_idx: which entry in ``schedules`` is the contract baseline (default 0 = first one). entitlement_milestone: optional task_code (e.g. "Ready for Takeover") — recorded on the result, not used for math. output_dir: optional dir for HTML dashboard / DOCX report. If "", a tempdir is used and dropped after — the dashboard / report paths in the response will point to the temp location (caller responsible for moving them). Returns: { "analysis": full dict from run_windows() with keys: "windows", "cumulative", "baseline_label", "data_dates", "attribution_summary", "mcpm_attribution", ..., "dashboard": path to HTML dashboard (server-side), "report": path to DOCX executive report (server-side), "baseline_stability": {"worst_severity", "has_block", ...} } On failure: {"error": "..."} with no schedules processed.
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  • Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.
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  • 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.
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  • Get FX trading windows — essential for understanding conversion delays and optimal execution timing. Returns market sessions and liquidity windows for a currency. Use this to understand: - **Delay diagnosis**: Payments arriving outside FX market hours for the target currency are held until the next trading session, adding hours or overnight delays. Critical for restricted currencies (INR, BRL, CNY, etc.). - **Rate optimization**: Higher liquidity = tighter spreads = better rates. Execute during peak windows to minimize conversion costs. Pass a currency code to get its optimal window, or omit to get all market sessions and overlap windows. Args: currency: ISO 4217 currency code (e.g., "EUR", "JPY"). Omit to get all sessions and overlaps. Examples: fx_timing_advisor("EUR") fx_timing_advisor("JPY") fx_timing_advisor("INR") # Check INR conversion windows fx_timing_advisor()
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  • Returns structured information about what the Recursive platform includes: features, AI model details, supported integrations, and what's included at every tier. Use for systematic feature comparison.
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  • Get basic information about a Compute Engine Commitment, including its name, ID, status, plan, type, resources, and creation, start and end timestamps. Requires project, region, and commitment name as input.
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  • Get content recommendations for an AWS documentation page. ## Usage This tool provides recommendations for related AWS documentation pages based on a given URL. Use it to discover additional relevant content that might not appear in search results. URL must be from the docs.aws.amazon.com domain. ## Recommendation Types The recommendations include four categories: 1. **Highly Rated**: Popular pages within the same AWS service 2. **New**: Recently added pages within the same AWS service - useful for finding newly released features 3. **Similar**: Pages covering similar topics to the current page 4. **Journey**: Pages commonly viewed next by other users ## When to Use - After reading a documentation page to find related content - When exploring a new AWS service to discover important pages - To find alternative explanations of complex concepts - To discover the most popular pages for a service - To find newly released information by using a service's welcome page URL and checking the **New** recommendations ## Finding New Features To find newly released information about a service: 1. Find any page belong to that service, typically you can try the welcome page 2. Call this tool with that URL 3. Look specifically at the **New** recommendation type in the results ## Result Interpretation Each recommendation includes: - url: The documentation page URL - title: The page title - context: A brief description (if available)
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  • Query vulnerabilities for multiple packages in one call — the primary tool for dependency audits, SBOM scanning, and lockfile triage. Pass an array of {name, ecosystem, version} tuples (up to 1000). Each entry in the response corresponds positionally to the input. Each finding includes CVE aliases for chaining to nist-nvd-mcp-server for CVSS scoring. Invalid ecosystem strings are rejected before querying — call osv_list_ecosystems to validate.
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  • Detect price manipulation in time-series data. Send a price or price+volume history as a numeric array. Early windows define 'normal' trading, recent windows are tested for manipulation patterns (pump-and-dump, spoofing, layering). Example: Send 90 days of closing prices → detect manipulated windows.
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