Dimensions Analytics

Search and analyze Dimensions research data: publications, grants, researchers, patents, trials

What does this entry provide?

Dimensions Analytics is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 73/100. 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 Dimensions Analytics 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: 73/100
Install method: npm
Repo: digital-science/dimensions-analytics-mcp
Repo updated: Sep 22, 2026

Install command

npx -y @digital-science-dsl/dimensions-analytics-mcp@1.4.2

Install method: npm

Review the upstream source before running this command.

GitHub project Homepage

Quality

Repo stars

Repo updated

Sep 22, 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": "2026-09-22T13:40:18.113882Z",
      "publishedAt": "2026-09-22T13:40:18.113882Z",
      "statusChangedAt": "2026-09-22T13:40:18.113882Z"
    }
  },
  "server": {
    "name": "ai.dimensions/analytics-mcp",
    "_meta": {
      "io.modelcontextprotocol.registry/publisher-provided": {
        "tags": [
          "research",
          "publications",
          "grants",
          "patents",
          "clinical-trials",
          "bibliometrics",
          "analytics"
        ]
      }
    },
    "title": "Dimensions Analytics",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "version": "1.4.2",
    "packages": [
      {
        "version": "1.4.2",
        "transport": {
          "type": "stdio"
        },
        "identifier": "@digital-science-dsl/dimensions-analytics-mcp",
        "registryType": "npm",
        "registryBaseUrl": "https://registry.npmjs.org",
        "environmentVariables": [
          {
            "name": "DIMENSIONS_API_KEY",
            "format": "string",
            "isSecret": true,
            "isRequired": true,
            "description": "Dimensions API key (same key as the Dimensions DSL API)"
          },
          {
            "name": "DIMENSIONS_BASE_URL",
            "format": "string",
            "description": "Dimensions API base URL. Required for custom instances, e.g. https://your-instance.dimensions.ai"
          }
        ]
      }
    ],
    "repository": {
      "url": "https://github.com/digital-science/dimensions-analytics-mcp",
      "source": "github",
      "subfolder": "apps/mcp"
    },
    "websiteUrl": "https://github.com/digital-science/dimensions-analytics-mcp#readme",
    "description": "Search and analyze Dimensions research data: publications, grants, researchers, patents, trials"
  }
}

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