Lambë

Shape-aware query language for structured data — JSON, YAML, TOML, HCL, CSV, Markdown.

What does this entry provide?

Lambë is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 51/100. 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 Lambë 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: 51/100
Install method: manual
Repo: hakimjonas/lambe
Repo updated: Sep 7, 2026

Install command

See source docs

Install method: manual

Review the upstream source before running this command.

GitHub project

Quality

Repo stars

Repo updated

Sep 7, 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.
Documentation (10) and description quality (10): parsed manifest or SKILL.md frontmatter, and a real description rather than a placeholder.

MCP manifest

{
  "_meta": {
    "io.modelcontextprotocol.registry/official": {
      "status": "active",
      "isLatest": true,
      "updatedAt": "2026-09-07T20:07:40.604567Z",
      "publishedAt": "2026-09-07T20:07:40.604567Z",
      "statusChangedAt": "2026-09-07T20:07:40.604567Z"
    }
  },
  "server": {
    "name": "io.github.hakimjonas/lambe",
    "title": "Lambë",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "version": "0.14.0",
    "packages": [
      {
        "transport": {
          "type": "stdio"
        },
        "fileSha256": "c1db000870dd5bb577098adb369df6745d6d64ac2ebd58076fe68340becdd729",
        "identifier": "https://github.com/hakimjonas/lambe/releases/download/v0.14.0/lam-mcp-linux-x64",
        "registryType": "mcpb"
      },
      {
        "transport": {
          "type": "stdio"
        },
        "fileSha256": "ce5c401cb9b123a69a78f072060d4aad5490541204a8a675037e63ad10b991fa",
        "identifier": "https://github.com/hakimjonas/lambe/releases/download/v0.14.0/lam-mcp-linux-arm64",
        "registryType": "mcpb"
      },
      {
        "transport": {
          "type": "stdio"
        },
        "fileSha256": "0baf613355a6a94ac18c4c37105ec7f29ab4007882e0af4a416dcbb49329e2ab",
        "identifier": "https://github.com/hakimjonas/lambe/releases/download/v0.14.0/lam-mcp-macos-x64",
        "registryType": "mcpb"
      },
      {
        "transport": {
          "type": "stdio"
        },
        "fileSha256": "f0281c296bcf89343c49f79581869a31559952cf0d180c19b5e0c69e9d6a15f5",
        "identifier": "https://github.com/hakimjonas/lambe/releases/download/v0.14.0/lam-mcp-macos-arm64",
        "registryType": "mcpb"
      },
      {
        "transport": {
          "type": "stdio"
        },
        "fileSha256": "ed63a299720bd75a409a5e1231f7fad327c04f5ea283bd8ffdc2f1c6fb80f008",
        "identifier": "https://github.com/hakimjonas/lambe/releases/download/v0.14.0/lam-mcp-windows-x64.exe",
        "registryType": "mcpb"
      }
    ],
    "repository": {
      "url": "https://github.com/hakimjonas/lambe.git",
      "source": "github"
    },
    "description": "Shape-aware query language for structured data — JSON, YAML, TOML, HCL, CSV, Markdown."
  }
}

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