cachebro
cachebro provides a local file cache for AI coding agents. It stores file versions in an embedded Turso/SQLite-compatible database, hashes file contents to detect changes, and returns either full content (first read), an 'unchanged' response, a unified diff for updated files, or partial unchanged/updated ranges for offset/limit reads. It can be run as a CLI that exposes an MCP server with caching tools, or used as a TypeScript SDK.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Local-first design with no described auth suggests reduced risk of external exposure, but increases reliance on local environment security. The cache persists file contents/diffs locally in an embedded database; this can be sensitive. No information is provided on transport security (TLS) for the MCP server, access controls, or how inputs/paths are validated.
⚡ Reliability
Best When
Single-user (or locally isolated) agent workflows where repeated reads of the same local files occur during multi-step coding tasks.
Avoid When
When you need rigorous security boundaries between different users/projects, or when local disk persistence of cached file data is not acceptable.
Use Cases
- • Reducing LLM token usage by avoiding repeated full-file reads
- • Providing compact diffs to agents during iterative coding/refactoring
- • Accelerating agent workflows in local editor integrations via MCP tooling
- • Tracking per-session read state to avoid redundant reads across a coding session
Not For
- • Production multi-tenant SaaS scenarios where multiple users need strong isolation and authentication
- • Use cases requiring remote file access across networks or centralized cache management
- • Environments that cannot allow local file hashing/caching of repository contents
Interface
Authentication
No authentication described. The MCP server appears intended for local use within a user's editor/agent environment.
Pricing
Open-source (MIT) and distributed via npm; no pricing model described.
Agent Metadata
Known Gotchas
- ⚠ If the underlying MCP server is not configured/enabled, the agent may fall back to built-in file reading tools.
- ⚠ The cache relies on file content hashing; large files or high churn may reduce savings.
- ⚠ Partial reads depend on offset/limit; if agents request different ranges each time, benefits may be smaller.
Alternatives
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Scores are editorial opinions as of 2026-03-30.