This release is a pre-release and may not be stable for production use.
agentgrep
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 fast prompt-history stores — ranked by relevance, deduped, with newest as the stable tie-break:
$ agentgrep search "deploy"
Use prompt matches to search selected conversations. Targeted search attempts at most 25 conversations by default and reports approximate coverage:
$ agentgrep search "deploy" --deep
Search prompt records across every readable conversation backend:
$ agentgrep search "deploy" --exhaustive
Search prompts and conversations together in one explicit deep sweep:
$ agentgrep search "deploy" --exhaustive --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="prompts",
any_term=False,
regex=False,
case_sensitive=False,
agents=agentgrep.AGENT_CHOICES,
limit=10,
effort="prompt",
)
result = agentgrep.run_search_result(Path.home(), query, backends=backends)
for record in result.records:
print(record.agent, record.title or record.path)
print(result.summary.status.state, result.summary.coverage)
Links
- Documentation: https://agentgrep.org/
- Source: https://github.com/tony/agentgrep
- Issues: https://github.com/tony/agentgrep/issues
- Changelog: CHANGES
- License: MIT
1 maintainer
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