mcp-codebase-intelligence
Provides a semantic understanding of your codebase by parsing with tree-sitter and building a graph of symbols and dependencies. Enables AI assistants to navigate code, analyze changes, and discover architecture using 18 tools with minimal context overhead.
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g-tiwari
Source: Glama
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LOG_LEVELLogging verbosity: debug, info, warn, error infoPROJECT_ROOTe =/path/to/your/projectPROJECT_ROOTSUse for projects spanning multiple repositories:Tool annotations
No tools have read-only/destructive annotations
Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.
All four hints declared on every tool
18/18 tools missing one or more hints — list_projects (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); switch_project (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); add_project (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +15 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.
For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.
Tool inputs are validated
15/18 tool handlers declare input schemas (83%)
Declare an inputSchema with zod/joi/yup on every tool definition.
Tool handlers catch errors
Only 0/18 tool handlers wrap calls in try/catch (0%)
Wrap each tool handler body in try/catch and return a structured error response.
Tool test coverage
Only 2/18 tools referenced in tests (11%)
Write tests that reference each tool by name so every tool has at least one test.
Shell command execution
1 child_process call — runs shell commands
Prefer library functions over shell-outs. If you must shell out, ensure all inputs are properly escaped.
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