Evidra

Evidra — Flight recorder for AI infrastructure agents

What does this entry provide?

Evidra is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 82/100. 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 Evidra to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: Official MCP Registry
Quality: 82/100
Install method: oci
Repo: Registry only
Repo updated: Mar 11, 2026

Install command

docker run -i --rm ghcr.io/vitas/evidra-mcp:0.4.7

Install method: oci

Review the upstream source before running this command.

Source entry

Quality

Repo stars

Repo updated

Mar 11, 2026

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.

MCP manifest

{
  "_meta": {
    "io.modelcontextprotocol.registry/official": {
      "status": "active",
      "isLatest": true,
      "updatedAt": "2026-03-11T14:14:54.466747Z",
      "publishedAt": "2026-03-11T14:14:54.466747Z",
      "statusChangedAt": "2026-03-11T14:14:54.466747Z"
    }
  },
  "server": {
    "name": "io.github.vitas/evidra",
    "title": "Evidra",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "version": "0.4.7",
    "packages": [
      {
        "transport": {
          "type": "stdio"
        },
        "identifier": "ghcr.io/vitas/evidra-mcp:0.4.7",
        "registryType": "oci",
        "environmentVariables": [
          {
            "name": "EVIDRA_ENVIRONMENT",
            "format": "string",
            "description": "Environment label (production, staging, development)"
          },
          {
            "name": "EVIDRA_EVIDENCE_DIR",
            "format": "string",
            "description": "Directory for evidence JSONL storage"
          },
          {
            "name": "EVIDRA_SIGNING_MODE",
            "format": "string",
            "description": "Signing mode: strict (default) or optional (ephemeral local mode)"
          },
          {
            "name": "EVIDRA_SIGNING_KEY",
            "format": "string",
            "isSecret": true,
            "description": "Base64-encoded Ed25519 private key (required for strict mode)"
          },
          {
            "name": "EVIDRA_SIGNING_KEY_PATH",
            "format": "string",
            "description": "Path to PEM-encoded Ed25519 private key (required for strict mode if key not inline)"
          }
        ]
      }
    ],
    "description": "Evidra — Flight recorder for AI infrastructure agents"
  }
}

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