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Turn any web API into a governed, auditable, agent-ready MCP server.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "CaskMCP" yet — see the docs or source repo.
I have a set of internal REST APIs that need to be safely exposed to AI agents. Using CaskMCP, design an MCP server plan covering endpoint mapping, lockfile approvals, permission boundaries, fail-closed enforcement, and audit logging.
An MCP integration plan showing how to convert internal APIs into controlled, auditable agent tools.
Explain how to use CaskMCP to expose a third-party payments API as an MCP tool, with a lockfile controlling allowed actions, parameter ranges, and version changes so unapproved calls are rejected.
An integration design with approval and constraint rules, clearly defining allowed scope, rejection conditions, and change governance.
We need to trace every external API call made by AI agents. Using CaskMCP, design a full audit approach covering request logs, approval linkage, failure events, accountability, and compliance records.
A complete auditing and tracing framework to support monitoring, accountability, and compliance.
Convert OpenAPI specs into MCP servers so AI agents can call APIs.
Let AI securely query and update case data through MCP tools.
Production-ready MCP server for query normalization, retrieval, and RAG prompt building.
Publish, author, and reuse AI tools and skills via MCP and REST.
Build and extend MCP servers with plugins for API-powered capabilities.
Run code securely in a WASM sandbox with capability manifests and task APIs.