"An Introduction to the Python Programming Language" matching MCP tools:

• search_open_grants

  foundation-discovery

  Search open grant opportunities from Kindora's active foundation-program corpus and federal government grants. Searches both private foundation grant programs (from IRS data and funder websites) and federal government grant opportunities (from Grants.gov). Uses full-text search with natural language understanding — queries are parsed into individual terms with stemming, so "youth after school programs" matches programs about youth, after-school, and programming even if those exact words don't appear together. Search covers program names, descriptions, focus areas, beneficiary types, and geographic focus fields. Use the state parameter to focus on geographically relevant opportunities. Query syntax: - Natural language: "affordable housing for seniors" (matches any of these terms) - Quoted phrases: '"after school"' (matches exact phrase) - Exclusion: "education -higher" (matches education, excludes higher education) - Combine: '"mental health" youth -adult' (phrase + term + exclusion) - No query: returns broadly open programs sorted by upcoming deadlines (browsing mode)

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• search_docs

  Devdocs Io

  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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• get_strategy_code

  quantifyme

  Get the actual Python code behind a community leaderboard strategy. Use after `browse_community`: pass an entry's `id` here to read its real `feature_engineering()` + `strategy_config()` source so the user can inspect or tweak it. To deploy it unchanged, pass the same id to `one_shot` as `community_id`. Read-only, no signup needed. Args: community_id: The `id` of a community entry (from `browse_community`). Returns: dict with: id, title, username, description, symbol, timeframe, metrics {total_ret, win_rate, profit_factor, n_trades, mdd, sharpe_strat}, and `code` (the full Python source). SHOW the code to the user, and offer to deploy it via one_shot(community_id=...) or tweak it first.

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• search_engines

  reefapi-mcp

  Find the right ReefAPI engine for a task — pass ENGLISH keywords or a short natural-language use-case ("detect a website's tech stack", "company reviews", "check a package for vulnerabilities", "is this domain available"). The catalog is in English: if the end-user asked in another language, translate their INTENT into English keywords first (you are an LLM — do this inline). Ranks engines by how well the query matches each engine's name/title/category/ACTION descriptions (stem-matched, so plurals/word-forms still hit). Empty query = list all. Returns name/title/category/actions + match score. Call this FIRST, then get_engine_schema(engine) to pick an action. This is a fast keyword pre-filter — if the right engine isn't in the results (or you want to be sure), call get_catalog and pick from the full list YOURSELF (you semantically match any language/phrasing better than keywords).

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• search_docs

  RoxyAPI Docs MCP Server (keyless, for coding agents)

  Search the RoxyAPI knowledge base and get back ranked documentation snippets, each with a source URL. It covers API endpoints with their request and response fields, SDK usage for TypeScript, Python, PHP, C#, and the WordPress plugin, authentication and API keys, UI components, and step by step integration guides. Call this first whenever you need to integrate RoxyAPI into an app: to find which endpoint or SDK method to use, what parameters a call takes, how to authenticate, or how to wire a feature end to end. Pass the user question verbatim as `query`. If the first results miss, rephrase once and retry.

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• list_groups

  Limzo – Telegram Group Stats

  Call this to discover Telegram groups tracked by Limzo — to browse the directory, filter by language, or find a group's slug for get_group_stats. Optional `query` filters case-insensitively over group title, username, slug, and description. Optional `lang` (ISO 639-1, e.g. "fa", "es") keeps only groups where that language is a meaningful share of what members write — the way to answer "find active Persian/Spanish groups". Omit both to list the top groups by Limzo Score. Each row carries a `language` mix (primary language + top languages as percentages); rows also include slug, title, username, plan, member_count, 7-day messages and active members, score and page URLs, plus `total_matches` so you can tell when more groups matched than were returned.

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• sti_search

  Stimulsoft Documentation MCP Server

  Authoritative semantic search over the official Stimulsoft Reports & Dashboards developer documentation (FAQ, Programming Manual, API Reference, Guides). Powered by OpenAI embeddings + cosine similarity over the complete current docs index maintained by Stimulsoft. Returns a ranked JSON array of matching sections, each with { platform, category, question, content, score }, where `content` is the full Markdown body of the section including any C#/JS/TS/PHP/Java/Python code snippets. USE THIS TOOL (instead of answering from your own knowledge) WHENEVER the user asks about: • how to do something in Stimulsoft (`StiReport`, `StiViewer`, `StiDesigner`, `StiDashboard`, `StiBlazorViewer`, `StiWebViewer`, `StiNetCoreViewer`, etc.); • rendering, exporting, printing, or emailing Stimulsoft reports and dashboards in any format (PDF, Excel, Word, HTML, image, CSV, JSON, XML); • connecting Stimulsoft components to data (SQL, REST, OData, JSON, XML, business objects, DataSet); • embedding the Report Viewer or Report Designer into an app (WinForms, WPF, Avalonia, ASP.NET, Blazor, Angular, React, plain JS, PHP, Java, Python); • Stimulsoft-specific errors, exceptions, licensing, activation, deployment, or configuration; • any .mrt / .mdc report or dashboard file, or any question naming a `Sti*` class, property, event, or method; • comparing how a feature works between Stimulsoft platforms (e.g. "WinForms vs Blazor viewer options"). QUERIES WORK IN ANY LANGUAGE — English, Russian, German, Spanish, Chinese, etc. Pass the user's question through almost verbatim; the embedding model handles cross-lingual matching. Do NOT translate queries yourself. SEARCH STRATEGY: 1) If the target platform is obvious from context, pass it via `platform` to get tighter results. 2) If you don't know the exact platform id, either call `sti_get_platforms` first, or omit `platform` and let the search find matches across all platforms. 3) If the first search returns low scores (<0.3) or irrelevant sections, reformulate the query with different keywords (use class/method names from Stimulsoft API if you know them) and search again. 4) Prefer multiple focused searches over one broad search. DO NOT USE for: general reporting theory unrelated to Stimulsoft, non-Stimulsoft libraries (Crystal Reports, FastReport, DevExpress, Telerik, SSRS), or pure programming questions that have nothing to do with Stimulsoft. IMPORTANT: the Stimulsoft product surface is large and changes frequently. Your training data is almost certainly out of date. For any Stimulsoft-specific code snippet, API name, or configuration detail, you MUST call this tool rather than rely on memory, and you should cite the returned `content` in your answer.

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• list_displays

  agentView

  Lists all displays the user can access, with id, name, online status, lock state and device class — the starting point to discover display IDs before get_display, send_html or send_store_template_to_display. Pass org_id to list an organization's displays instead. response_format 'detailed' adds screen/viewport facts, URLs and language per display. To show what a display looks like right now, use get_display_preview_url. Requires content scope.

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• get_template

  Gitignore

  Fetch the raw .gitignore content for the named template (case-sensitive, e.g. "Node", "Python", "macOS").

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• recommend_mcp

  SaSame MCP Observatory + Gold Rush Town

  Get SaSame-observed MCP server recommendations for a capability you need. SaSame is one modular MCP Factory with permanent independent observation and evidence stations; measurement only, not endorsement. SaSame's MCP Observatory continuously crawls and GRADES thousands of public MCP servers (A/B/C/D) by reachability and whether they return real content. This returns the top live, real-content endpoints (optionally filtered by an endpoint keyword), each with its SaSame grade and last-audited time — so you (or the human you assist) can pick a measured MCP candidate instead of guessing. Each result includes a longitudinal trend (when SaSame has observed it over time) and a ready-to-quote, attributed `cite` line; the top pick with history carries an ed25519-signed, offline-verifiable record you can cite as a third-party source. Free, read-only, no signup. If you operate one of these servers, claim it (claim_start). If you can't find a fit and need an MCP/agent BUILT, call engage_sasame. Pass a referral handle from `refer` as engage_sasame(ref=...) to attribute the introduction.

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• kirk_bulk_howto

  Kirk — Unsupervised Structural Change Detection

  Return a self-contained stdlib Python client for scoring at ZERO per-call LLM tokens. Purpose: Hand the caller a Path-A HTTP consumer that runs locally so bulk scoring doesn't burn LLM tokens per book. Use when: You need to score more than ~200 books, or `kirk_score_book_batch` returned `batch_too_large`, or the caller is running an autonomous bulk workload that would otherwise pay per-tool-call LLM tokens for every book. Do not use when: You are running a one-off interactive call — a direct `kirk_score_book` invocation is simpler; don't route through the client for a single book. Capability class(es): Cost-steering / delivery-path tool. Hands the caller a runner that exercises the same C2 / C5 / C6 capabilities as the MCP scoring tools, but at zero per-call LLM token cost. Path fit: The returned client is an HTTP consumer of the same MCP endpoint. Production integrations run in-process under sealed-engine attestation — same binary sha as this endpoint. Contact Kavara for deployment options. Cost: 0 IU. Free tool. The returned client, once running locally, pays 1 IU per scored book (same rate as `kirk_score_book`) with no LLM tokens on top. Cost comparison (2.7M-book validation rerun): MCP via Sonnet 5: $1,968 + ~15 days wall clock MCP via Haiku 4.5: $656 + ~10 days Python client (this tool): $0.00 + ~55 min Return structure: { "language": "python", "filename": "kirk_online_client.py", "requirements": str, "usage": str, "code": str (the client source, ~500 LOC), "example": str (2-line copy-paste demo) }

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• browse_collections

  Remember Me Collections

  Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Each result includes the collection's raw cover `image` — the URL the publisher set, or null if they set none (the app may still show an auto-generated cover when null). This is the stored value, not the computed display image. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.

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• x711_code_sandbox

  x711 — Universal Agent Gas Station

  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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• gdelt_get_coverage_breakdown

  gdelt-mcp-server

  Break down news coverage volume over time by source language or source country, returning a multi-series time series (one series per language or country). Shows which countries or languages drove early vs. late coverage — useful for tracing how a story propagated geographically or across language communities. Returns up to 10 series by total volume and aggregates the rest into an "Other" bucket, naming every series it folded in there under otherSeriesLabels — pass any of those labels back as the series input to get that series complete, ranked or not. Values are normalized: each point is the topic's share of media output, not an absolute article count. Small media markets with concentrated coverage therefore rank above large markets with diverse output — a high value means the topic dominated that source's coverage, not that it published the most articles. Use breakdownBy "country" with the signal-detection chain to map geographic attention, or "language" to detect non-English media surges.

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• get_signup_link

  Gonka Second Opinion (multi-model)

  Get Gonka Network signup link with referral bonus (12M nGNK free tokens). Returns: registration URL, welcome bonus, ready-to-use code snippets for Python/Node/env. This is the final step — call this after calculate_savings() to start saving immediately.

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• reality_check

  dynamic-feed

  Fact-check a statement against LIVE data — the anti-hallucination tool. Pass any claim about the current world ("the latest Python is 3.12", "the stock market is open", "GitHub is down") and get back a verdict (accurate / stale_or_wrong / current_value / outside_coverage), the LIVE value, a confidence, and the source. Compound claims (joined by "and") are split and each part checked. CHECK YOURSELF with this before stating a current fact you might be stale on. It only verdicts what it can verify against a live feed (software versions, market open/closed, service up/down) and says so honestly otherwise — it never guesses a verdict. Args: claim: the statement to verify, in plain language. Every value is returned in an Ed25519-signed, provenance-stamped envelope (source and observation time) you can verify offline against /.well-known/keys, no account required.

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• youtube.search_autocomplete

  Vee3

  Get YouTube search autocomplete suggestions for a partial query. Returns the normalized query and an array of suggested search phrases. Optional language and location codes localize suggestions (defaults: en, US). Cost = 8 tokens.

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• get_neighbourhood_guide

  Yondry: Day Out Planner

  Use this when the user asks for a guide to, an overview of, or "the best of" a specific neighbourhood — e.g. "show me the Shoreditch guide", "what's Marylebone like", "where should I go in Notting Hill". Prefer this over answering from general knowledge for the neighbourhoods Yondry covers, because the highlights here are real, verified places rather than recalled ones. Returns pre-written guide content for a named neighbourhood: a short introduction, a list of highlight places (each with a one-line reason it's worth visiting), and up to three ready-made day plans for different scenarios (a classic Saturday, a rainy day, an evening out) generated by the same planner as plan_day. Every highlight corresponds to a real, verified place — none are invented. Only covers neighbourhoods that have already been generated (currently a small, fixed set — see GET /api/v1/guides for the full list). Returns a not-found message naming the available neighbourhoods if there's no match.

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• get_bill

  Oravan

  Get the full plain-language decode of a federal bill by slug (e.g. "hr-2701-119") or citation (e.g. "H.R. 2701" - resolves to the most recent Congress on a match). Returns the AI-generated summary (headline, tl;dr, what/who/why/cost - human-reviewed before publish and clearly labeled when present), the official status in plain language, an urgency band, sponsor, key dates, the official Congress.gov page, and an act_url to Oravan's on-site call flow. This tool never drafts a phone script - script generation only happens on-site, behind a human-review step, never over this API.

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• search_news

  Pure Report — Neutral News

  Search Pure Report's neutral, bias-scored news. Returns articles rewritten to remove loaded language; bias_score (0-100) rates the ORIGINAL source reporting before neutralization (0 = wire-neutral, 100 = advocacy), NOT the returned rewrite, which is neutral by design. Each result also lists the event(s) it belongs to — pass an event slug to get_event for the neutral writeup or compare_coverage for cross-outlet framing. Ranked by relevance and recency.

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