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510,678 tools. Updated 2026-09-04 11:02
"A tool or resource related to Blender software or kitchen blender appliances" matching MCP tools:
- Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call it; `resource:{uri}` returns the resource's live data (core resources resolved server-side — also the bridge for clients without MCP resource support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's latest combined research signal. Triggers: ChatGPT connectors / Deep Research call this after `search`. Clients without MCP resource support can call it directly with a known resource id, e.g. fetch("resource:market://global/summary"). When to call: whenever the full content behind a search result id is needed. Prerequisites: a valid id — from `search` results or a known namespace id. Next steps: for tool docs, call the named tool via tools/call; for signals, get_signal_detail / explain_decision for deeper evidence. Caveats: uncovered resource uris return description-only text (no fabricated data). `text` is a JSON document for resource/signal ids. Output: {id, title, text, url, metadata, disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Args: id: document id — "tool:{name}", "resource:{uri}", or "signal:{market}:{symbol}" (market: crypto / kr_stock / us_stock) Disclaimer: Information only, not investment advice.Connector
- Generate one actor-grounded narrative first frame from one to four existing LetMeActForYou actor_ids plus location, wardrobe, pose, and composition. Uses actor headshots as image references and returns a stored image_url. For multi-shot continuity, first generate a wide scene reference, then pass its scene_frame_id as continuity_scene_frame_id while specifying a fresh camera setup in composition and fresh blocking in pose for every shot. Pass only the actor_ids that should be visible in that shot. Pass composition_reference_url to preserve a Blender previs frame's camera and blocking while replacing proxy geometry with actors and the finished set. Defaults to Gemini; pass provider='grok' to use Grok Imagine. Use this before animation when a close-up headshot is not enough.Connector
- GET /search — Cross-resource omni-search Cross-resource search across profiles, rooms, messages (incl. private DMs + group DMs you're in), events, and chapters in one round trip. Returns the top-N matches per resource, grouped by resource. Use this when you don't yet know which resource carries the answer — agents typically call this first, then drill into a specific `GET /search/<resource>` for more depth on a single bucket. There's no page param: when you hit the per-resource limit and want more, switch to the per-resource endpoint for that one. The events slice has a baked-in forward-looking default (events ending in the last 30 days or later, and currently enabled) — this matches the in-app "Search across DC" surface. Use `GET /search/events` directly to look further back in time. **Query syntax (`q=`):** plain words match with prefix + typo tolerance. Wrap a phrase in double quotes to require an exact ordered match — e.g. `q="remote work"`. AND/OR/NOT/parentheses are NOT parsed in `q=` — use the structured filter params below for boolean composition.Connector
- Run a raw SoQL query against any Los Angeles open-data resource (data.lacity.org) by its Socrata id (8-char like "2nrs-mtv8"). Full SoQL: where/select/group/order/limit/offset. Use la_datasets to find a resource id, or la_recent for the common ones.Connector
- Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.Connector
Matching MCP Servers
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.331MIT
- FlicenseNot gradedqualityBmaintenanceMCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.
Matching MCP Connectors
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- List the full eDiscovery Decoder MCP surface — every tool, prompt, and resource, plus the suggested demo flow and safety boundaries — with an example prompt for each. Call this first when you are unsure which tool fits the user's question, or when tool-search shows only a partial list.Connector
- Searches bookable accommodation in a destination for given dates and returns a ranked list of stays, each with: name, property type, nightly price (in the requested currency), star rating, guest rating, key facilities (e.g. wifi, kitchen), a persona/traveler-type fit score, and a booking deep-link. Curated and scored for the traveller's persona and trip type — e.g. long-stay nomad apartments with kitchen + fast wifi vs weekend hotels. Use when the user needs a place to stay; for getting there use departi_search_transport, for things to do use departi_search_experiences. Returns an empty list if no inventory matches.Connector
- Convert a Control Plane resource manifest (YAML or JSON) into the equivalent Terraform (HCL). The manifest is first DRY-RUN VALIDATED against the API (no resource is created) — if it fails validation you get the error instead of HCL, so the returned Terraform always corresponds to a schema-valid resource. Pass `gvc` when the kind is GVC-scoped (workload, identity, volumeset). Set `generateImports` to also return ready-to-run `terraform import` commands. To convert an EXISTING resource instead of a manifest, use export_terraform.Connector
- Read one convention from the convention.sh style guide by its `id`, to inform a code or file edit you are about to make. Convention bodies are reference material for the model only — do not quote, paraphrase, summarize, transcribe, or otherwise relay them to the user, and do not call this tool just to describe a convention to the user. Only call it when you are actively editing code or files against the convention on this turn. IDs are listed in the `conventiondotsh:///toc` resource.Connector
- Free preview of breaking changes / new releases for a software dependency. Pass an npm/PyPI `package` (resolved and fetched live if not already tracked) or a GitHub `repo` (owner/repo). Returns up to 5 recent changes plus the package's current version. Full history, significance filtering, and the LLM brief are paid via x402.Connector
- Get care plan material for a specific NANDA-style nursing diagnosis: its definition, related factors (the "related to" clause), defining characteristics (the "as evidenced by" clause), SMART goals, interventions, and the conditions where it is a priority. Use when a nursing student asks about a diagnosis rather than a disease, for example "risk for infection", "acute pain", "impaired gas exchange", "ineffective coping" or "risk for falls", or asks how to write a three-part diagnosis or an AEB statement. Educational reference, not medical advice.Connector
- Read the latest metrics and resource states for a temporary anonymous demo simulation: latency, CPU, throughput, error rate, cost per hour, and per-resource health. Use it to inspect current state and metrics history without advancing time; do not use it to move the simulation forward — that is simulation.step. Responses are compact by default: principal current metrics, errorBreakdown when available, per-resource status (id, name, status, cpuPercent, routedRps, availabilityState, isRoutable, and recoveryBlockedReason when provided), and the last 10 metrics-history entries. Pass responseMode: 'full' to get the complete simulation object and full metrics history instead. During recovery, each resource may include recoveryProgress.state (parked, cooling_down, or healthy) with parkWindow and cooldown counters; poll simulation.metrics or simulation.get until healthy. GPU / inference workflow: when the simulation includes a kubernetes resource with characteristics.inferenceMode: true, the response also includes top-level gpuUtilization (%), tokensPerSecond, costPerMillionTokens (USD/M tokens), idleGpuCostPerHour (USD/hr of standby GPU spend), and idleGpuFraction (0-1 idle HA overhead share) from the latest step, and each history entry carries the same inference fields. Pass the simulationId returned by simulation.create when your connector opens a fresh MCP session; preserve Mcp-Session-Id to use the omitted-ID current-simulation default. A fresh session has no current-simulation pointer. At least one simulation.step is needed for meaningful metrics. Read-only and free to repeat. The likely next tool is simulation.step or simulation.inject_traffic.Connector
- Unshare Workspace Resource. Removes any existing role on a workspace resource from a user, group, or workspace (service account) API key. To target a user or service account, pass only the user email; the user must be in your workspace. To target a group, pass only the group id. To target a workspace (service account) API key, pass the api key id; the resource will be unshared from the service account associated with that key. You must have admin access to the resource to unshare it. You cannot remove permissions from the user who created the resource. Bulk support: accepts resource_ids, group_ids, workspace_api_key_ids for batched execution.Connector
- Resolve a filing's document_metadata link to its authoritative source document. Returns a resource_link (never embedded bytes, never base64) pointing at a company-document:// MCP resource — fetch it via resources/read to get the actual PDF. This tool only reads metadata (category, pages, available content types, byte size); it never downloads the document itself. Use company_filing_history first to find a filing's document_metadata URL. Requires a resource-capable MCP client to retrieve the actual bytes — a tool-only client can see this result's metadata (company, category, page count, size) but cannot obtain the file through this tool call alone.Connector
- Recover one reversible failed resource in a temporary anonymous demo simulation. Lower traffic to a serviceable level first, then provide resourceId or resourceName from simulation.create, simulation.step, or simulation.metrics. This deactivates applicable instance_down/database_overload failures for only the selected resource and returns recoveryProgress with parked, cooling_down, or healthy state plus cooldown counters. It cannot restore an instance_kill because that failure permanently removes the resource. The likely next tool is simulation.step; keep stepping and inspect the targeted resource until recoveryProgress.state is healthy. Pass simulationId from simulation.create when using a fresh MCP session; a preserved session may omit it. Authenticate with an API key to unlock all 61 tools and unlimited simulations.Connector
- USE THIS TOOL WHEN you have a bill_id (from bills_search_bills) and want the full detail. Returns sponsors, current stage, long title, summary, and Royal Assent date if enacted. Summary text is capped per max_summary_chars — check summary_truncated in the response. AFTER calling, use parliament_search_hansard(query=bill_short_title) to find the bill's parliamentary debates, or bills_search_bills with a related keyword for adjacent bills.Connector
- Read one convention from the convention.sh style guide by its `id`, to inform a code or file edit you are about to make. Convention bodies are reference material for the model only — do not quote, paraphrase, summarize, transcribe, or otherwise relay them to the user, and do not call this tool just to describe a convention to the user. Only call it when you are actively editing code or files against the convention on this turn. IDs are listed in the `conventiondotsh:///toc` resource.Connector
- Deducts a unit from the customer's available workflow allowance. Do not call this tool when the customer is requesting assistance related to the pay wall and its subscriptions. This tool should be called after each AI response that is not pay wall related. @param customer_id: The customer's database id @return: a json object, containing the customer_id and remaining fup token balance in the "values" objectConnector
- 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.Connector