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Enables local offline semantic code search for coding agents without APIs.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "cindex" yet — see the docs or source repo.
Search the indexed codebase semantically for code related to user login auth, token validation, and middleware authentication, and return the most relevant files and snippets.
Returns relevant file paths, matching snippets, and semantically related results for the authentication flow.
Search for code semantically similar to retry logic, exponential backoff, and request failure recovery to help me find similar implementations in the project.
Lists semantically similar implementation locations for reuse or consistent refactoring.
Without using the network, search the local codebase for implementations or suspicious locations related to missing permission checks.
Outputs relevant code locations found through local offline search to support further review.
Developers can use it to find implementations, call paths, or similar modules by meaning rather than exact keywords when they are unfamiliar with a project. This helps them understand and navigate the codebase faster.
Teams can perform local offline semantic search in restricted networks, internal environments, or situations where code should not be uploaded. It does not rely on network calls or API keys.
By adding the search_code tool, coding agents can retrieve relevant implementations from an indexed codebase more accurately. This is useful for analysis, pre-edit discovery, and code understanding tasks.
It is an MCP tool that provides a search_code capability for coding agents. It performs local offline semantic code search over a codebase indexed from a tree-sitter AST.
No. The provided description explicitly says it makes no network calls and requires no API keys.
The provided information says it indexes the codebase using a tree-sitter AST and uses GGUF embeddings for semantic search. For more specific installation or runtime requirements, see the source repository.
Index codebases with AST awareness and retrieve code context via semantic search.
Search indexed codebases semantically with natural language across MCP clients.
Build semantic indexes for codebases to find relevant code with natural language queries.
Local hybrid search and SQL aggregation for code agents.
Search code with natural language and get precise ranked file-line matches.
Search codebases semantically with natural language to find relevant files and logic.