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304,762 tools. Last updated 2026-07-16 07:24

"A server for the yfinance Python library for downloading financial market data" matching MCP tools:

  • Get the full schema for one petal_components component: attrs, slots, defaults, allowed values, and a working HEEx usage example. Call this every time you are about to write a tag like <.button>, <.modal>, <.table>, or <.field> so the attrs and slots match the real library instead of training-data guesses.
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  • 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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  • 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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  • AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'
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  • Find which documentation SETS exist whose NAME matches a substring (e.g. "python" → Python 3.x, "react" → React). Returns doc SETS, NOT their content — this does NOT look up a function/method/API name. To search inside a doc for an entry like "Array.map" or "fetch", use search_index (slug + query).
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  • Add a missing tool to the aiaam.xyz catalog. Provide its PyPI project or GitHub repo URL; the registry builds an unverified MAI-1 contract from public metadata only (no invented data). Idempotent — if the tool already exists, its current contract is returned. Use this when search_tools returns no results for a library you know exists.
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  • Give your AI agent a phone. Place outbound calls to US businesses to ask, book, or confirm.

  • Verified market data for AI trading agents: quality-flagged candles, funding, OI, order flow. x402.

  • Get the Senzing JSON analyzer script to validate mapped data files client-side. REQUIRED: `workspace_dir` (writable directory, e.g. ~/sz-workspace) — the call WILL FAIL without it. The analyzer validates records against the Entity Specification, examines feature distribution, attribute coverage, and data quality. Returns a Python script (no dependencies) with instructions. No source data is sent to the server. Typical workspace_dir values: Linux `/tmp` or `~/sz-workspace`; macOS `~/sz-workspace`; sandboxed envs: explicit path under home (do NOT assume /tmp exists).
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  • Get a personalized market news briefing based on your validated edge library. Profiles your strategies, searches today's news for the instruments and setups you actually trade, and writes a concise digest connecting each headline to your specific book. Each news item includes a ↳ line tying it to your actual positions and edges (e.g. 'your ES momentum setups', 'your GC mean-reversion edge'). Requires at least 5 strong edges in your library. Costs credits.
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  • Fetch the raw .gitignore content for the named template (case-sensitive, e.g. "Node", "Python", "macOS").
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  • Fetch WHOIS registration data for a domain. Returns a JSON object keyed by WHOIS server host name. Each value contains parsed fields such as Domain Name, registrar details, dates, name servers, domain status, DNSSEC data, and raw text lines. Set include_registrar to true to query registry and registrar servers (slower, more complete). Default false queries the registry server only. Cost = 4 tokens.
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  • Post a sanitized market signal brief to Slack via incoming webhook. Proprietary data policy enforced server-side: price levels, EMA values, and raw indicator readings are stripped — only direction labels, confidence %, regime, risk level, and text thesis are delivered to Slack. Pass webhook_url to target your own Slack channel, or omit to post to the SML shared channel (requires SLACK_WEBHOOK_URL env var on this server). Free.
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  • Get a time-limited download link to a company's official Jahresabschluss document. Read-only. Parameter: - doc_key (required): a filing's `document_ref` ("{fnr}:{stichtag}") from get_company_details, a bare FNR (-> latest filing), or a legacy doc_key. Returns `download.url`, a short-lived signed link (open it, don't expect bytes inline), plus the `financial_institution` flag + caveat for banks/insurers, whose figures live only in the PDF. `download` is null if nothing is ingested for that filing. Use to fetch the original filing artifact; for the already-parsed figures use get_company_details / get_full_record instead of downloading.
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  • Screen the tracked large-cap universe by market cap, trailing P/E, dividend yield, and sector — returns matching stocks ranked by market cap. A raw market-data filter; for a ranked, fundamentals-driven screen pair this with financial-signals-mcp's composite_value_score. PAID: $0.01 USDC per query after a daily free allowance. On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=<signature>. An Authorization: Bearer fnet_ key bypasses payment.
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  • Execute JavaScript or Python code in an isolated sandbox. Use for: data processing, math, CSV parsing, JSON transformation, crypto calculations, algorithm testing. Secure — no filesystem access, no network. Returns: { output: string, runtime_ms: number, language: string }. Requires API key.
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  • Extract tables and forms as Markdown from a PDF or image (base64-encoded). Use when the document contains structured tabular data such as financial statements, data sheets, or forms. For plain prose documents, use extract_text instead. Returns: { pages: number, text: string } — text contains Markdown-formatted tables. Example prompts: - "Extract the tables from this financial statement." - "Pull the data table from this PDF into Markdown format." - "Get the tabular data from this form document."
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  • Download all attachments for an inbound email as a gzip-compressed tar archive. Returns the archive as a base64-encoded string along with the attachment count and SHA-256 digest. Prefer getEmail first to check the attachment manifest before downloading.
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  • Pause (turn off) a connected account: stop downloading new mail while KEEPING everything already brought in. `account` is the connected email address. Reversible with resume_email_account. Confirm with the user before pausing — it stops their email from updating.
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  • The unit tests (code examples) for HMR. Always call `learn-hmr-basics` and `view-hmr-core-sources` to learn the core functionality before calling this tool. These files are the unit tests for the HMR library, which demonstrate the best practices and common coding patterns of using the library. You should use this tool when you need to write some code using the HMR library (maybe for reactive programming or implementing some integration). The response is identical to the MCP resource with the same name. Only use it once and prefer this tool to that resource if you can choose.
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  • Mandatory initialization step for any session against the Blockscout MCP server. Returns server reference data plus the `blockscout-analysis` skill pointer and URI resolution rule. MANDATORY FOR AI AGENTS: Call this tool first in every session. The returned payload identifies where the operating rules and analysis framework live and how to read referenced skill files before executing further tool calls.
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  • Mandatory initialization step for any session against the Blockscout MCP server. Returns server reference data plus the `blockscout-analysis` skill pointer and URI resolution rule. MANDATORY FOR AI AGENTS: Call this tool first in every session. The returned payload identifies where the operating rules and analysis framework live and how to read referenced skill files before executing further tool calls.
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