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138,191 tools. Last updated 2026-05-20 07:07

"A server to add framework documentation and use a cursor agent to search it" matching MCP tools:

  • Search npm or PyPI to estimate how crowded a package category is before you claim that a market is empty, niche, or competitive. Use this when you have a category or search phrase such as 'edge orm' and want live result counts plus representative matches. Do not use it to compare exact known package names or to infer adoption from downloads; it reflects search results, not market share. Registry responses are cached for 5 minutes.
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  • Return who the server sees you as on this MCP session. Use this when you're unsure whether you're authenticated — typically right after register_agent_poll returns approved, to confirm that the current session is now bound to the new agent without having to poke a write tool. Also useful as a first-call diagnostic on any fresh MCP connection. Response: auth: 'anonymous' | 'authenticated' auth_kind: 'mcp_session_binding' | 'bearer' | 'session' | 'signature' | 'none' user_id?: string agent?: { slug, display_name, description?, profile_url } account_type?: 'agent' | 'human'
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  • Chat with the Roboflow AI agent. Use this tool for: - **Roboflow Q&A** — the agent has the full Roboflow documentation indexed (SDKs, REST API, deployment options, training, batch processing, Universe, blocks, pricing, etc.). Ask it anything about how Roboflow works. - **Advanced workflow building** — workflows complex enough that direct block composition via ``workflow_blocks_*`` is impractical. The agent knows every block and connection pattern. - **Solution planning** — pass ``mode="plan"`` and the user's problem; the agent uses a stronger planning model to scope a CV solution end-to-end before any building happens. For straightforward workflows you can construct yourself, the direct ``workflow_*`` tools are fine — you don't have to route every workflow through the agent. ## Conversation flow The agent runs a multi-step conversation. It may ask clarifying questions, recommend a model, or (in plan mode) produce a plan for confirmation. Pass the returned ``conversation_id`` back on follow-up calls to keep context. Use ``agent_conversations_list`` and ``agent_conversation_get`` to find and resume past conversations. ## CRITICAL: the agent NEVER publishes workflows Every workflow the agent creates or edits is saved as a **draft**. The published version that callers using the workflow by id will hit is unchanged until you explicitly publish. To make agent edits live, call ``agent_workflow_publish`` with the workflow ``url`` returned in the chat response. ## Running an agent-built workflow Two options: 1. **Run the draft directly without publishing** — pass the ``specification`` returned in the chat response to ``workflow_specs_run``. Best for testing the draft, or for one-off runs where you don't want to disturb the currently-published version. 2. **Publish, then run by id** — call ``agent_workflow_publish(workflow_url=...)`` then ``workflows_run(workflow_id=..., images=...)``. Use this when you want the change to go live for everyone using the workflow by id. ## Where to open a workflow in the Roboflow UI The agent's ``text`` response may include URLs pointing at the workflow in the Roboflow UI. **Ignore those URLs** — the agent sometimes picks the wrong host or path. Each workflow in the ``workflows`` array has an ``app_url`` field with the correct, environment-aware URL (built from the current ``APP_URL`` plus ``/{workspace}/solutions/chat?workflowUrl=...``) — show that one to the user instead. ## Response shape - ``text`` — the agent's reply. - ``workflows`` — workflows created or edited in this turn, each with ``id``, ``name``, ``url`` (slug), ``app_url`` (clickable Roboflow UI URL — use this), and ``specification`` (the full draft JSON; pass it to ``workflow_specs_run`` to execute without publishing). - ``conversation_id`` — pass back to continue the conversation.
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  • Save a fact or note into the agent's memory. Use scope to choose visibility: 'workspace' = visible to every agent in this workspace (use for shared facts, project conventions); 'agent' = private to this agent (use for personal working notes); 'thread' = scoped to one conversation (use for thread-specific reminders); 'person' = scoped to one contact (use for per-contact context). If a note with the same key+scope exists it will be updated. Do NOT use this tool for behavioral rules or corrections — use feedback.save for those.
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  • Retrieves authoritative documentation directly from the framework's official repository. ## When to Use **Called during i18n_checklist Steps 1-13.** The checklist tool coordinates when you need framework documentation. Each step will tell you if you need to fetch docs and which sections to read. If you're implementing i18n: Let the checklist guide you. Don't call this independently ## Why This Matters Your training data is a snapshot. Framework APIs evolve. The fetched documentation reflects the current state of the framework the user is actually running. Following official docs ensures you're working with the framework, not against it. ## How to Use **Two-Phase Workflow:** 1. **Discovery** - Call with action="index" to see available sections 2. **Reading** - Call with action="read" and section_id to get full content **Parameters:** - framework: Use the exact value from get_project_context output - version: Use "latest" unless you need version-specific docs - action: "index" or "read" - section_id: Required for action="read", format "fileIndex:headingIndex" (from index) **Example Flow:** ``` // See what's available get_framework_docs(framework="nextjs-app-router", action="index") // Read specific section get_framework_docs(framework="nextjs-app-router", action="read", section_id="0:2") ``` ## What You Get - **Index**: Table of contents with section IDs - **Read**: Full section with explanations and code examples Use these patterns directly in your implementation.
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  • [IN DEVELOPMENT] [READ] Search the Layer 3 curated directory of MCP servers and agent-work tools. The directory has 30 entries across three vetting tiers — `first-party` (operated by the swarm.tips DAO), `vetted` (third-party, we've used + verified), `discovered` (cataloged from public sources, not yet exercised). Filter by `query` (substring vs name/description/tags), `category` (substring), and `tier`. Results sort first-party → vetted → discovered. The same directory powers swarm.tips/discover; this tool exposes it programmatically. Use this when an agent needs to find an MCP server for a capability (DeFi, search, browser automation, etc.) instead of an opportunity (which `discover_opportunities` covers).
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Matching MCP Servers

Matching MCP Connectors

  • Connect any two AI agents and let them talk directly. Claude to Claude, Claude to OpenAI, or any MCP-compatible agent

  • Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.

  • 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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  • Register a new agent account and get an API key. No authentication needed. The returned API key grants read+write access to all BorealHost API endpoints. Store it securely — it cannot be retrieved again. The key is automatically activated for this session — all subsequent tool calls will use it. No extra configuration needed. If no email is provided, a synthetic agent identity is created (agent-{uuid}@api.borealhost.ai). If an email is provided, it links to an existing or new human account. Args: name: Human-readable name for this API key (default: "Agent Key") email: Optional email to link to a human account Returns: {"api_key": "bh_...", "key_id": "uuid", "prefix": "bh_...", "scopes": ["read", "write"], "account_id": "uuid", "message": "Store this API key securely..."} Errors: RATE_LIMITED: Max 5 registrations per IP per hour VALIDATION_ERROR: Invalid email format
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  • Interleaved cross-org release feed for a collection — same shape as `get_latest_releases` but scoped to the collection's member orgs. Cursor-paginated: pass `limit` for slice size (default 20), `cursor` to continue from a prior call. The result's `_meta.pagination` carries `kind: 'cursor'`, `hasMore`, and `nextCursor` when more rows exist; the response text echoes `nextCursor` so an LLM caller can chain without parsing `_meta`. Cursors are stable under inserts.
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  • Use this tool when a user wants to change something about a plan you've already generated. Trigger phrases: 'can we compress to X weeks', 'remove the QA pod', 'add a data-migration workstream', 'what if we use AI agents instead of a QA team', 'split this into a phase 1 / phase 2', 'what would it look like with half the team', 'can we drop scope to fit a smaller pack', 'add Salesforce integration to the plan'. Requires the plan_id from a prior plan_vdc call. Returns the updated plan with adjusted pods, roles, modules, Delivery Units, and recommended Delivery Pack.
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  • Reverse-lookup a single concept ID (MITRE ATLAS technique like 'AML.T0051', OWASP LLM Top 10 risk like 'LLM01', OWASP Agentic Top 10 issue like 'ASI03', or ISO 42001 Annex A clause like 'A.6') across the AI Defense Matrix. Returns which framework the concept belongs to, the asset rows whose alignment cites it, the cells whose evaluation cellPrompts cite it, and those prompts themselves. Useful when a vendor's product is defined by a specific technique ('we defend AML.T0051') and they need to find which matrix cells to claim. Recognizes only concepts with structured IDs; for prose-only frameworks (NIST IR 8596, CSA AICM, Google SAIF, OWASP AI Exchange) use aidefense_get_framework_alignment instead. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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  • Lists every workspace the user can access, with workspace_id, uniqueName (slug), and display name. Behavior: - Read-only. Page size 20, sorted by name. Pass nextCursor back as cursor to fetch the next page. - Optional search matches against name, uniqueName (slug), member emails, and website (case-insensitive); empty results return an empty array. - Other perspective tools accept either workspace_id or uniqueName interchangeably. - Returns description for each workspace — use it to match the right workspace based on context. - Does NOT mark which workspace is the caller's default — call workspace_get_default once and compare ids client-side if you need to highlight it. When to use this tool: - The user names a specific workspace and you need its workspace_id (filter with search). - Showing the user the full set of workspaces they can pick from. When NOT to use this tool: - You just need the user's default workspace — use workspace_get_default. - You already have a workspace_id and want details — use workspace_get.
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  • Orient yourself: list available doc categories and their namespaces. Use once at session start (or when unsure) before applying a `category=` / `namespace=` filter to `browse` / `semantic_search`. NOT a content search. Categories: `natives` (PLAYER, ENTITY, VEHICLE, …), `vorp`, `rsgcore`, `oxmysql`, `discoveries` (AI, weapons, peds, animations, clothes, objects, …), `jo_libs` (menu, notification, callback, framework-bridge, …, dev_resources, redm_scripts), `guides`, `learnings`.
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  • Lists perspectives — either browsing one workspace or searching by title across every workspace the user can access. Items include perspective_id, title, status, conversation count, and workspace info. Behavior: - Read-only. - Browse mode (workspace_id, no query): lists every perspective in that workspace. - Search mode (query): matches against the perspective title across accessible workspaces. Optional workspace_id narrows the search. Query must be non-empty and ≤200 chars. - Errors with "Please provide workspace_id to list perspectives or query to search." if neither is given. - Pass nextCursor back as cursor; has_more indicates further results. When to use this tool: - Resolving a perspective_id from a name the user mentioned (search mode). - Browsing a workspace's perspectives to pick or summarize. When NOT to use this tool: - Inspecting one known perspective in detail — use perspective_get. - Aggregate counts or rates — use perspective_get_stats. - Fetching conversation data — use perspective_list_conversations or perspective_get_conversations. Examples: - List all in a workspace: `{ workspace_id: "ws_..." }` - Search by name across all workspaces: `{ query: "welcome" }` - Search within a workspace: `{ query: "welcome", workspace_id: "ws_..." }`
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  • Add one or more tasks to an event (task list). Supports bulk creation. IMPORTANT: Set response_type correctly — use "text" for info collection (names, phones, emails, notes), "photo" for visual verification (inspections, serial numbers, damage checks), "checkbox" only for simple confirmations. NOTE: To dispatch tasks to the Claude Code agent running on Mike's PC, use tascan_dispatch_to_agent instead — it routes directly to the agent's inbox with zero configuration needed.
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  • Get a list of all available themes with style descriptions and recommendations. Call this to decide which theme to use. Returns a guide organized by style (dark, academic, modern, playful, etc.) with "best for" recommendations. After picking a theme, call get_theme with the theme name to read its full documentation (layouts, components, examples) before rendering. This tool does NOT display anything to the user — it is for your own reference when choosing a theme.
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  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
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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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  • List the registry of platform skills — discrete how-to guides for one specific task each (e.g. 'gate-an-endpoint', 'add-a-cron-job', 'add-rag-search'). Each entry is a name, one-line purpose, and category. Use this to find the right skill, then call `read_skill(name)` to load the full pattern. When in doubt about how a Hatchable feature works, **list_skills first**. The skills are the canonical, agent-tested patterns. They beat guessing or reading the verbose docs. Filter by `query` (matches name + purpose) or `tag` (auth, data, ai, ops, etc.). Without filters, returns the full registry (~35 entries).
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  • Returns the full three-step Demand Discovery validation framework: (1) Market Research, (2) Demand Discovery Report with the Demand Score and Build/Pivot/Kill verdict, (3) Agentic Launch (90-day continuous outreach). Use when a user asks "how do I validate an idea?", "what's the methodology?", or wants to understand the structured approach. Built on the "behavior over opinion" principle. Trigger phrases: "what's the framework", "demand discovery framework", "what's the methodology", "how does demand discovery work", "step by step validation", "what's the process", "how to structure validation", "validation framework", "validation methodology", "structured validation", "show me the framework", "explain the methodology".
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