agentgrep

mcp
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SUMMARY

Search history local agents for prompts and conversations (Codex, Claude, Cursor, agy, grok, pi, opencode)

README.md

agentgrep

PyPI version
Python versions
License: MIT

Read-only search for local AI agent prompts and opt-in conversations
across Codex, Claude Code, Cursor, Gemini, Antigravity, Grok, Pi, OpenCode, and VS Code.

agentgrep provides a CLI and an MCP server over the same discovery + parsing layer:

  • A terminal CLI (agentgrep) with a Textual TUI for interactive
    browsing of normalized records.
  • An MCP server (agentgrep-mcp) that exposes search, discovery,
    catalog, and validation tools to any client that speaks Model
    Context Protocol.

Pre-alpha. APIs may change.

Install

$ uvx agentgrep --help

Other install methods (pipx, uv add, pip install) and full setup
snippets live in the
installer widget on agentgrep.org/cli/.

CLI quickstart

Search your prompts across every configured agent — ranked, deduped,
newest first:

$ agentgrep search "deploy"

Search prompts and conversations together in one sweep:

$ agentgrep search "deploy" --scope all

Prefer ripgrep-shaped flags? grep mirrors rg / ag against the
same records:

$ agentgrep grep "deploy" --scope conversations

Stream JSON so a non-MCP agent or shell pipeline can consume the
results:

$ agentgrep find --json

Open the read-only Textual explorer, seeded with a query:

$ agentgrep ui "deploy"

--json and --ndjson make every command pipe-friendly, and any
search-shaped subcommand takes --ui to hand the same query to the
explorer (e.g. agentgrep grep "deploy" --ui). Agents that don't
speak MCP can drive the CLI directly; see
https://agentgrep.org/cli/ for the per-subcommand reference.

MCP server: quickest setup

In Claude Code:

$ claude mcp add agentgrep -- uvx --from agentgrep agentgrep-mcp

For Claude Desktop / Codex / Cursor / Gemini snippets, see
https://agentgrep.org/mcp/.

Library quickstart

from pathlib import Path

import agentgrep

backends = agentgrep.select_backends()
query = agentgrep.SearchQuery(
    terms=("hello",),
    scope="all",
    any_term=False,
    regex=False,
    case_sensitive=False,
    agents=agentgrep.AGENT_CHOICES,
    limit=10,
)
for record in agentgrep.run_search_query(Path.home(), query, backends=backends):
    print(record.agent, record.title or record.path)

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