nervapack
01MCP server Claude CodeCodexCursor
MCP server "nervapack" as configured in ramdhavepreetam/NervaPack. Launched with nervapack-mcp. Needs 1 environment variable to run.
MCP server Claude CodeCodexCursor
MCP server "nervapack" as configured in ramdhavepreetam/NervaPack. Launched with nervapack-mcp. Needs 1 environment variable to run.
MCP server Claude CodeCodexCursor
MCP server "nervapack-memory" as configured in ramdhavepreetam/NervaPack. Launched with nervapack-memory-mcp.
Instructions file
Claude Code instructions for ramdhavepreetam/NervaPack, covering nervapack — claude code instructions, always use nervapack mcp tools, mcp servers available, project essentials and release checklist.
Command
Remove ingested graph data and start fresh.
Command
Analyze file-level import dependencies, detect circular dependencies, and visualize the dependency graph.
Command
Check system configuration and NervaPack dependencies.
Command
Add semantic doc-to-code edges to an existing graph without full re-ingestion.
Command
Extract and visualize the N-hop neighbourhood of a specific file, class, or function.
Command
View your query history and aggregate token-savings analytics.
Command
Show the files changed most frequently in git history — high-churn areas often indicate bug-prone or rapidly-evolving parts of the codebase.
Command
Build the knowledge graph from your codebase.
Command
Inspect and manage the NervaPack agent memory store from the command line.
Command
Search the knowledge graph using natural language.
Command
Show a one-screen summary of cumulative token savings across all queries.
Command
Launch an interactive web dashboard for your knowledge graph — graph health, query analytics, code hotspots, and graph evolution, all in one place.
Command
Show the health and current state of the local NervaPack graph.
Command
Incrementally update the graph after code changes — without re-ingesting the whole project.
Command
Render the knowledge graph as an interactive, standalone HTML file.
MCP server Claude CodeCodexCursor
MCP server for Google's TimesFM 2.5 foundation model — give any AI agent zero-config time-series forecasting. Runs locally from the timesfm-mcp Python package.