Security sidecar between an AI coding agent and everything it touches — MCP servers, LLM APIs, SSH, subprocess env. Release mirror; development is private.
Universal security sidecar for AI agents.
agent-sidecar sits between your AI coding agent and everything it touches — MCP tool servers, LLM APIs, SSH hosts, databases — enforcing security policy, brokering short-lived credentials, scanning for prompt injection, and recording every action in a keyed, hash-chained audit trail.
It proxies real MCP servers: one persistent process per upstream with a proper initialize handshake, real tool schemas passed through, and policy applied to every call. LLM tool calls are enforced for Anthropic and OpenAI in both streamed and buffered responses — neither stream: false nor n: 2 is a way around policy. A stream whose shape it does not recognise is forwarded and says so, in the log and in the audit trail, rather than leaving you quietly unprotected.
Where a surface is not covered in a given session, the wrapper says that too, inline and in the closing summary. A run that guarded nothing must not look like a run that guarded everything.
Surface How Status --------- MCP tools Persistent session per upstream server, real handshake, real inputSchema. Tools re-advertised as .; policy, secrets and audit on every call Working — run reports it plainly when it finds no MCP config to take over Every MCP scope Claude Code is launched with --strict-mcp-config, so a wrapped session reads only the config agent-sidecar generates — user, local and project scopes are all covered, and no config file is modified at all Working — the scope list is measured against the real binary by scripts/probereality.sh, not read off documentation. Agents without the f
From the project README.
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An OKF-backed Model Context Protocol (MCP) server delivering persistent long-term memory and SQLite FTS5 search for AI agents.
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