Create up to 50 tags in a project in one call. Returns per-item results (created / skipped). Duplicates are matched case-insensitively on name. Confirm with the user before calling — this mutates project data.
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130,071 tools. Last updated 2026-05-06 21:22
"Generating a module in an iOS Xcode project using MVP with Coordinator architecture" matching MCP tools:
- Complete Disco signup using an email verification code. Call this after discovery_signup returns {"status": "verification_required"}. The user receives a 6-digit code by email — pass it here along with the same email address used in discovery_signup. Returns an API key on success. Args: email: Email address used in the discovery_signup call. code: 6-digit verification code from the email.Connector
- Soft-delete up to 50 tags in a project. Removes tag associations from prompts. Returns per-item results (deleted / skipped). This is destructive — always confirm with the user before calling.Connector
- Export a generated image asset by session and asset ID. Returns the image inline as base64 along with metadata (format, dimensions, size). When running locally (stdio transport), you can optionally provide a destinationPath to save the image to disk. USAGE: After generating an image with generateImage, use the sessionId and assetId to export: exportImageAsset(sessionId="...", assetId="...") To save to disk (local/stdio only): exportImageAsset(sessionId="...", assetId="...", destinationPath="/Users/me/project/images/logo.png")Connector
- Create a new sncro session. Returns a session key and secret. Args: project_key: The project key from CLAUDE.md (registered at sncro.net) git_user: The current git username (for guest access control). If omitted or empty, the call is treated as a guest session — allowed only when the project owner has "Allow guest access" enabled. brief: If True, skip the first-run briefing (tool list, tips, mobile notes) and return a compact response. Pass this on the second and subsequent create_session calls in the same conversation, once you already know how to use the tools. After calling this, tell the user to paste the enable_url in their browser. Then use the returned session_key and session_secret with all other sncro tools. If no project key is available: tell the user to go to https://www.sncro.net/projects to register their project and get a key. It takes 30 seconds — sign in with GitHub, click "+ Add project", enter the domain, and copy the project key into CLAUDE.md.Connector
- Repay debt to an Arcadia lending pool using tokens from the wallet (requires ERC20 allowance). To repay using account collateral instead (no wallet tokens needed), use write_account_deleverage. Check allowance first (read_wallet_allowances), then approve the pool if needed (write_wallet_approve). Check outstanding debt with read_account_info.Connector
Matching MCP Servers
- AlicenseAqualityBmaintenanceUnified MCP server for Xcode + iOS Simulator — build, deploy, screenshot, and interact with your iOS app from Claude Code, Cursor, or any MCP client. Built in Swift. Single binary. No Node/Python runtime required.Last updated67MIT
- AlicenseAqualityBmaintenanceEnables interaction with iOS simulators by providing tools to inspect UI elements, control UI interactions, and manage simulators through natural language commands.Last updated143,2531,946MIT
Matching MCP Connectors
Agent Module provides structured, validated knowledge bases engineered for autonomous agent consumption at runtime. Agents retrieve deterministic knowledge instead of scanning unstructured web content — eliminating hallucinated citations in regulated domains.
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- Scaffold an api/<route>.js that takes a prompt and returns the model's response, using lib/llm.js so every call lands in the llm_calls table for free observability. Produces: - POST handler with requireAuth - body: { prompt, model? } - calls llm.run({ user_id, purpose, prompt, model, system }) - returns { text, usage, llm_call_id } Example: add_llm_endpoint({ route: 'summarize', purpose: 'summarize', system_prompt: 'Summarize the user\'s text in 2-3 sentences.' }) Note: The project must have lib/llm.js (it ships in tpl-prompt-playground; copy if needed).Connector
- Creates a visual edit session so the user can upload and manage images on their published page using a browser-based editor. Returns an edit URL to share with the user. When creating pages with images, use data-wpe-slot placeholder images instead of base64 — then create an edit session so the user can upload real images.Connector
- Restore an authenticated session using a previously saved JWT token. Call this at the start of a new session before any other tools, using a token saved from a prior check_login call. If the token is invalid, fall back to login.Connector
- Cancel a public booking using the bookingToken. Only works for bookings in pending_confirmation, scheduled, or confirmed status. Optionally include a reason. Does NOT require an API key. The booking token scopes access to a single booking.Connector
- Fetches the complete markdown content of an Apollo documentation page using its slug, or everything after https://apollographql.com/docs. Documentation slugs can be obtained from the SearchDocs tool results. Use this after ApolloDocsSearch to read full pages rather than just excerpts. Content will be given in chunks with the totalCount field specifying the total number of chunks. Start with a chunkIndex of 0 and fetch each chunk.Connector
- Get Secureship API authentication instructions. Call this FIRST before generating any code examples with authentication headers. Secureship uses X-API-KEY header authentication, NOT Bearer tokens.Connector
- Enforce a guardrail: verify an agent action against a compiled policy using formal verification. An SMT solver — not an LLM — determines whether the action satisfies every rule. Returns SAT (allowed) or UNSAT (blocked) with extracted values and a cryptographic ZK proof that the check was performed correctly. Cannot be jailbroken. 1 credit ($0.01). Requires api_key. Tip: end the action with an explicit claim like 'I assert this complies with the policy' for best extraction.Connector
- Delete an instance from a project. The request requires the 'name' field to be set in the format 'projects/{project}/instances/{instance}'. Example: { "name": "projects/my-project/instances/my-instance" } Before executing the deletion, you MUST confirm the action with the user by stating the full instance name and asking for "yes/no" confirmation.Connector
- Fetch Bitrix24 app development documentation by exact title (use `bitrix-search` with doc_type app_development_docs). Returns plain text labeled fields (Title, URL, Module, Category, Description, Content) without Markdown.Connector
- Save a file (PDF, PPTX, DOCX, etc.) to a client's record in the broker's CRM. Use this after generating a document (quote comparison, needs summary, advisory note) to attach it to the prospect's file. The client must already exist as a lead (use save_lead first). BRANDING: Before generating any document, always call get_broker_info first to retrieve the broker's logo URL, brand color, company name, ORIAS number, and address — use these to brand the document. The file content must be base64-encoded.Connector
- Run a read-only SQL query in the project and return the result. Prefer this tool over `execute_sql` if possible. This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE` statements and stored procedures aren't allowed. If the query doesn't include a `SELECT` statement, an error is returned. For information on creating queries, see the [GoogleSQL documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax). Example Queries: -- Count the number of penguins in each island. SELECT island, COUNT(*) AS population FROM bigquery-public-data.ml_datasets.penguins GROUP BY island -- Evaluate a bigquery ML Model. SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`) -- Evaluate BigQuery ML model on custom data SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Predict using BigQuery ML model: SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Forecast data using AI.FORECAST SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips', timestamp_col => 'date', id_cols => ['usertype'], horizon => 30) Queries executed using the `execute_sql_readonly` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `project_id` field.Connector
- What went wrong last time we touched this module? Returns past incidents, deploy failures, gotchas, and active constraints for a module or system. Use BEFORE modifying infrastructure code, deploy scripts, or any module with a history of fragility. Surfaces the kind of tribal knowledge that prevents repeat failures — Docker bind mount traps, Vault agent write patterns, stale dist/ artifacts, port conflicts, and similar operational landmines.Connector
- Get an upload URL to upload a single image to a project. Returns a pre-built upload URL and instructions. The caller must perform the actual upload using curl since the MCP server cannot access local files. This endpoint uploads images only. To add annotations, call annotations_save with the image ID from the upload response. For bulk uploads with annotations, use images_prepare_upload_zip.Connector
- Get a fast suitability score (0-100) for a US property without generating a full report. Call this when the user wants a quick go/no-go assessment or an initial screening before committing to a full analysis. Returns a single score with confidence level and one-sentence rationale.Connector