Persistent project memory for AI coding agents: one compact digest instead of re-reading the repo.
Persistent project memory for AI coding agents: one compact digest instead of re-reading the repo.
Every AI coding session starts the same way: the agent has no memory of your project, so it re-reads files, re-derives your architecture, or asks you to re-explain decisions you made months ago. You pay for that in tokens, time, and wrong guesses — every single session, on every machine, for every teammate.
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{ "mcpServers": { "projectmind": { "command": "npx", "args": ["-y", "@nodemint/projectmind", "mcp"] } } }Configuration as documented by the project. Restart the client after saving.
Read, search and edit files inside allowed directories with the Model Context Protocol reference Filesystem server.
Retrieve version-aware library documentation and code examples with Context7 MCP, using resolve-library-id and query-docs.
Use Microsoft’s Playwright MCP server to navigate pages, inspect accessibility snapshots, fill forms and capture browser screenshots.
Connect GitHub MCP to repositories, issues and pull requests with GitHub’s hosted service or a locally run server.
Use the Supabase MCP server to inspect database schemas, query project data and retrieve docs through a project-scoped connection.
Search Linear issues and projects, inspect work context and manage updates through Linear’s hosted MCP server with OAuth.