"author:jitendrakumar-ai" matching MCP servers:

Enables AI IDEs and coding agents to navigate code at the AST symbol level, perform surgical, collision-free refactoring, and resolve live library documentation. It also supports project onboarding memory, giving agents semantic precision without regex guesswork or heavy dependencies.

Enables AI coding agents to retrieve compact structural codebase context through repository architecture summaries, AST symbol extraction, cyclomatic complexity scoring, and TODO/FIXME hotspot search.

Enables AI agents and LLMs to persist facts, preferences, and observations in a local SQLite store and to build and traverse subject-predicate-object knowledge graphs across sessions. It provides fuzzy keyword search and graph queries so assistants retain context and recall prior project history without repeating prompts.

Enables AI agents and assistants to inspect live system telemetry, check TCP port connectivity, audit environment variables for leaked secrets, analyze and summarize log files, and list Docker containers — all with token-efficient, compressed output.