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127,233 tools. Last updated 2026-05-05 11:26

"Developing a Flutter application with embedded React Native" matching MCP tools:

  • Is this specific multi-package version combo verified to work together? USE WHEN: pinning a stack (next@15 + react@19 + node@22); before recommending a version matrix. RETURNS: {compatible, conflicts[], notes}.
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  • FS AI RMF Adoption Stage reference — INITIAL, MINIMAL, EVOLVING, EMBEDDED — public mode returns framework stages only. Connect org MCP or the dashboard questionnaire for org-scoped classification, control counts, and remediation priorities.
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  • FS AI RMF Adoption Stage reference — INITIAL, MINIMAL, EVOLVING, EMBEDDED — public mode returns framework stages only. Connect org MCP or the dashboard questionnaire for org-scoped classification, control counts, and remediation priorities.
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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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  • Captures the user's project architecture to inform i18n implementation strategy. ## When to Use **Called during i18n_checklist Step 1.** The checklist tool will tell you when to call this. If you're implementing i18n: 1. Call i18n_checklist(step_number=1, done=false) FIRST 2. The checklist will instruct you to call THIS tool 3. Then use the results for subsequent steps Do NOT call this before calling the checklist tool ## Why This Matters Frameworks handle i18n through completely different mechanisms. The same outcome (locale-aware routing) requires different code for Next.js vs TanStack Start vs React Router. Without accurate detection, you'll implement patterns that don't work. ## How to Use 1. Examine the user's project files (package.json, directories, config files) 2. Identify framework markers and version 3. Construct a detectionResults object matching the schema 4. Call this tool with your findings 5. Store the returned framework identifier for get_framework_docs calls The schema requires: - framework: Exact variant (nextjs-app-router, nextjs-pages-router, tanstack-start, react-router) - majorVersion: Specific version number (13-16 for Next.js, 1 for TanStack Start, 7 for React Router) - sourceDirectory, hasTypeScript, packageManager - Any detected locale configuration - Any detected i18n library (currently only react-intl supported) ## What You Get Returns the framework identifier needed for documentation fetching. The 'framework' field in the response is the exact string you'll use with get_framework_docs.
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  • Returns the Parquet schema for all tables in the Valuein SEC data warehouse. Includes table descriptions, column names, types, primary keys, and foreign-key references. Use this tool to understand the data model before querying with other tools. No data reads required — schema is embedded in the manifest. Available on all plans.
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  • Manage your Canvas coursework with quick access to courses, assignments, and grades. Track upcomin…

  • Conversational access to advertising performance data, creative analysis, and campaign insights

  • FS AI RMF Adoption Stage reference — INITIAL, MINIMAL, EVOLVING, EMBEDDED — public mode returns framework stages only. Connect org MCP or the dashboard questionnaire for org-scoped classification, control counts, and remediation priorities.
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  • Cell polygon as a native MCP EmbeddedResource (mimeType application/geo+json). Properties carry centre lat/lng, bbox, approx size in metres, and the 8-cell neighbourhood — drop straight into Mapbox / Leaflet / Deck.gl / QGIS without a GIS pipeline. When to use: Call when the agent (or a downstream renderer) needs the cell as geographic geometry — for map overlays, polygon-clipping ops, or feeding a styling pipeline. Pass `cell` as cell64 or place name. The result is a GeoJSON Feature with Polygon geometry; for a FeatureCollection that includes every recalled fact's value as a property, fetch /v1/cells/{cell64}/recall_geojson?bands=... over plain REST instead.
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  • Browse the knowledge base by technology tag at the START of a task. Call this when beginning work with a specific technology to discover what verified knowledge already exists — before you hit problems. Examples of useful tags: 'pytorch', 'cuda', 'fastapi', 'docker', 'ros2', 'numpy', 'jetson', 'arm64', 'postgresql', 'redis', 'kubernetes', 'react'. Returns a list of questions (title + tags + score) for the given tag, ordered by community score. Call `get_answers` on relevant results.
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  • Fetch a single article by slug — full intro, body, FAQ, references, embedded reviewers + authors with credentials, and pre-formatted citation strings (AMA, APA, Chicago).
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  • FS AI RMF Adoption Stage reference — INITIAL, MINIMAL, EVOLVING, EMBEDDED — public mode returns framework stages only. Connect org MCP or the dashboard questionnaire for org-scoped classification, control counts, and remediation priorities.
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  • Retrieves authoritative documentation for i18n libraries (currently react-intl). ## When to Use **Called during i18n_checklist Steps 7-10.** The checklist tool will tell you when you need i18n library documentation. Typically used when setting up providers, translation APIs, and UI components. If you're implementing i18n: Let the checklist guide you. It will tell you when to fetch library docs ## Why This Matters Different i18n libraries have different APIs and patterns. Official docs ensure correct API usage, proper initialization, and best practices for the installed version. ## How to Use **Two-Phase Workflow:** 1. **Discovery** - Call with action="index" 2. **Reading** - Call with action="read" and section_id **Parameters:** - library: Currently only "react-intl" supported - version: Use "latest" - action: "index" or "read" - section_id: Required for action="read" **Example:** ``` get_i18n_library_docs(library="react-intl", action="index") get_i18n_library_docs(library="react-intl", action="read", section_id="0:3") ``` ## What You Get - **Index**: Available documentation sections - **Read**: Full API references and usage examples
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  • Encode LayerZero TYPE_3 options bytes for use with EndpointV2.quote() and EndpointV2.send(). TYPE_3 (version tag 0x0003) is the current standard options format for LayerZero V2. Builds binary options with executor worker ID 0x01 and option type 1 (lzReceive) with configurable gas limit and native token drop amount. Returns the hex-encoded options bytes.
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  • Resolve a RedM/RDR3 SCRIPT native by hash or name — O(1), exact. Use whenever you see `Citizen.InvokeNative(0x...)`, `Citizen.invokeNative('0x...')`, `GetHashKey('NAME')`, or a SCREAMING_SNAKE_CASE native name (e.g. `SET_ENTITY_COORDS`, `GetPedHealth`) in Lua/JS/TS. NOT for game-data hashes (weapon/ped/animation names) — use `grep_docs`. Pass `hash` (0x… optional, case-insensitive) or `name` (exact first, ILIKE substring fallback). Returns name, hash, namespace, return type, params, description, full content, plus `findings[]` — community gotchas linked to that native. Inspect `findings[].id` and call `get_document({path: 'learning:<id>'})` for full body.
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  • Resolve a RedM/RDR3 SCRIPT native by hash or name — O(1), exact. Use whenever you see `Citizen.InvokeNative(0x...)`, `Citizen.invokeNative('0x...')`, `GetHashKey('NAME')`, or a SCREAMING_SNAKE_CASE native name (e.g. `SET_ENTITY_COORDS`, `GetPedHealth`) in Lua/JS/TS. NOT for game-data hashes (weapon/ped/animation names) — use `grep_docs`. Pass `hash` (0x… optional, case-insensitive) or `name` (exact first, ILIKE substring fallback). Returns name, hash, namespace, return type, params, description, full content, plus `findings[]` — community gotchas linked to that native. Inspect `findings[].id` and call `get_document({path: 'learning:<id>'})` for full body.
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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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  • Search the National Drug Code (NDC) directory by labeler company, brand name, product NDC, or application number. Returns labeler name, brand name, generic name, dosage form, route, active ingredients, DEA schedule, listing type, and packaging details. Drug products are not linked by FEI; use this tool with company name to find drugs at a company. Related: fda_search_drugs (application-level data with submissions), fda_drug_labels (full product labeling), fda_search_nsde (NSDE cross-reference).
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  • Fetch a single article by slug — full intro, body, FAQ, references, embedded reviewers + authors with credentials, and pre-formatted citation strings (AMA, APA, Chicago).
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