codemogger
codemogger indexes local source code by parsing it with tree-sitter, chunking into semantic units, embedding chunks with a provided/local embedding pipeline, and storing vectors plus full-text search in a single embedded SQLite (.db) file; it also provides an MCP server and CLI for indexing/reindexing and searching that index.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Designed for local execution with no API keys, which reduces remote credential exposure. However, it ingests arbitrary local source code and runs local embedding computation; security concerns primarily relate to supply-chain and dependency hygiene plus handling of local filesystem inputs. No information provided about sandboxing, safe path handling, or how errors/logs may include paths/content.
⚡ Reliability
Best When
You want an on-device, agent-friendly code search/indexing capability with a single-file SQLite database and a local embedding model.
Avoid When
You need a networked API with remote authentication/tenancy controls or require strict guarantees about data retention policies beyond local storage.
Use Cases
- • Local semantic search over a codebase for relevant definitions (functions/types/impls/classes).
- • Keyword lookup for identifiers with fast FTS-backed search.
- • Helping AI coding agents navigate unfamiliar repositories and retrieve relevant code snippets.
- • Offline codebase indexing and search without external services/API keys.
Not For
- • Use as a hosted/realtime SaaS search service.
- • Use where you require centralized access control/audit across multiple users without local isolation.
- • High-concurrency multi-tenant environments (it’s oriented around local single-user .db usage).
Interface
Authentication
No auth described; designed to run locally with no API keys. MCP server is intended to be spawned locally (e.g., via npx).
Pricing
No hosted pricing information provided; package is MIT and intended for local/offline use.
Agent Metadata
Known Gotchas
- ⚠ Embedding model runtime/latency: initial indexing can be dominated by local embedding compute (potentially long-running MCP calls).
- ⚠ Index lifecycle: agents should ensure they call index/reindex before searching relevant code.
- ⚠ Local file permissions/paths: MCP/CLI operate on local directories and write/read .db files; path mismatches can lead to empty/incorrect results.
- ⚠ Indexing respects .gitignore; agents expecting full traversal may miss ignored files.
Alternatives
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Scores are editorial opinions as of 2026-03-30.