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Private Agent memory and governed shared knowledge.
Agent Recall Trail is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 54/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. No automated install command is listed; check the repository for manual setup instructions. Review the last-pushed date and repository status before adding Agent Recall Trail to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
See source docsReview the upstream source before running this command.
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2026-10-02T02:55:30.468681Z",
"publishedAt": "2026-10-02T02:55:30.468681Z",
"statusChangedAt": "2026-10-02T02:55:30.468681Z"
}
},
"server": {
"name": "io.github.fantasyce/agent-recall-trail",
"title": "Agent Recall Trail",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
"version": "0.3.7",
"packages": [
{
"version": "0.3.7",
"transport": {
"type": "stdio"
},
"fileSha256": "ae9688371305c222d056c3f99aa2216d3555d386525593e0f234e1ac8e42be50",
"identifier": "https://github.com/fantasyce/agent-recall-trail/releases/download/v0.3.7/agent-recall-trail_0.3.7.mcpb",
"registryType": "mcpb"
}
],
"repository": {
"url": "https://github.com/fantasyce/agent-recall-trail",
"source": "github"
},
"websiteUrl": "https://fantasyce.github.io/agent-recall-trail/",
"description": "Private Agent memory and governed shared knowledge."
}
}