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An MCP server that validates content against MCP specification using semantic search and AI
io.github.carlisia/mcp-factcheck is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 63/100. 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. The install command above is ready to copy. Review the last-pushed date and repository status before adding io.github.carlisia/mcp-factcheck to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
docker run -i --rm ghcr.io/carlisia/mcp-factcheck:v1.0.0Review the upstream source before running this command.
{
"_meta": {
"io.modelcontextprotocol.registry/official": {
"status": "active",
"isLatest": true,
"updatedAt": "2025-10-07T05:23:36.272365Z",
"publishedAt": "2025-10-07T05:23:36.272365Z",
"statusChangedAt": "2025-10-07T05:23:36.272365Z"
}
},
"server": {
"name": "io.github.carlisia/mcp-factcheck",
"$schema": "https://static.modelcontextprotocol.io/schemas/2025-09-29/server.schema.json",
"version": "1.0.0",
"packages": [
{
"transport": {
"type": "stdio"
},
"identifier": "ghcr.io/carlisia/mcp-factcheck:v1.0.0",
"registryType": "oci",
"environmentVariables": [
{
"name": "OPENAI_API_KEY",
"isRequired": true,
"description": "OpenAI API key for embedding generation and content validation"
}
]
}
],
"repository": {
"url": "https://github.com/carlisia/mcp-factcheck",
"source": "github"
},
"description": "An MCP server that validates content against MCP specification using semantic search and AI"
}
}