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Meta Data MCP

by derekslinzversion 2.5.0i★ –iRuns on your computer
Registry nameio.github.derekslinz/meta-data-mcp

Install

Overview

Description from the maker (original English)

Query 76 open data APIs — government, science, finance, environment, and more.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: SSE
  • Category: Law & government data

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "meta-data": {
      "command": "uvx",
      "args": [
        "meta-data-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add meta-data -- uvx meta-data-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "meta-data": {
      "command": "uvx",
      "args": [
        "meta-data-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "meta-data": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "meta-data-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account derekslinz, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Law & government datai

  • More stars than 0% of the other 1744 servers in this category
  • Published to the registry more recently than 10% of the other 1744 servers in this category
  • Basic checks equal to or better than 100% of the other 1744 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Meta Data MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (2.5.0) reached the registry 6 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Lintsure, Premium Data MCP Server, Patents Trademarks Ip MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Lintsure

by lintsure

Compliance readiness checks for code: EU AI Act, GDPR, SOC 2, ISO 27001. Local. Not legal advice.

Runs on your computerUpdated today
Install

Premium Data MCP Server

by thenextgennexus.com

Government contracts, business registration, FDA recalls and product-price data as agent tools.

Runs in the cloudUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

meta-data-mcp

A single MCP server that transparently routes user requests to 90 open-data sources.

meta-data-mcp is one MCP server — not many. Under the hood it bundles 90 *plugins*, each wrapping a different open-data API. The plugins are an implementation detail; from your LLM's perspective there is one server and one place to ask "where can I find data about X?"

You install one server. You get all the data, discoverable through built-in routing tools.

Why "meta"?

Finding open data isn't the hard part — there's an absurd amount of it available. The hard part is finding the right dataset *when you need it*. meta-data-mcp makes that automatic:

  • The LLM calls opendata_providers_find ("FX rates", "court rulings", "earthquakes near Lisbon") and the server routes the query against an internal registry of every bundled plugin.
  • The LLM then calls the matching tool directly. No setup step in between, no separate servers, no per-provider install rituals.

This project was forked from opendata-mcp and reshaped around the single-server idea once the catalogue passed a few dozen plugins.

Installation

You'll need uv (a Python package manager).

# macOS — install uv via Homebrew so MCP clients can find it

brew install uv

Linux

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows (PowerShell)

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Then register the server with every MCP client installed on your machine:

uv run meta-data-mcp setup

The command auto-detects which MCP clients you have installed and adds one meta-data-mcp entry under mcpServers in each. Supported clients:

ClientConfig file
Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.json (macOS) / %APPDATA%/Claude/claude_desktop_config.json (Windows)
Claude Code~/.claude.json
Cursor~/.cursor/mcp.json
Windsurf~/.codeium/windsurf/mcp_config.json
Gemini CLI~/.gemini/settings.json
LM Studio~/.cache/lm-studio/mcp.json

Each existing config is backed up to .bak before writing. Restart the affected client(s) and you'll see one new server with discovery tools available immediately; plugin tools can then be activated on demand.

Inspect what's detected / configured on your machine:

uv run meta-data-mcp clients

Target a single client (or write to every supported client regardless of detection):

uv run meta-data-mcp setup --client claude-code

uv run meta-data-mcp setup --client all

If you want to see the JSON snippet without touching any config file (e.g. to paste into a client we don't support yet):

uv run meta-data-mcp setup --print-json

When META_DATA_MCP_AUTH_TOKEN is set, --print-json also surfaces the SSE-client snippet (with the real token) to stderr so you can wire a remote client.

Hosting meta-data-mcp as a remote SSE server

For deploying behind your own domain with bearer-token authentication, see docs/hosting.md. It covers systemd, Caddy/nginx TLS termination, token rotation, and the threat model.

CLI

There is one server, so the CLI takes no "provider" argument. Every command operates on the one meta-data-mcp server.

CommandWhat it does
uv run meta-data-mcp runRun the server (default SSE; pass --transport stdio for Claude Desktop).
uv run meta-data-mcp setupRegister the server in detected MCP client configs (or one target via --client).
uv run meta-data-mcp removeUnregister the server from detected MCP client configs (or one target via --client).
uv run meta-data-mcp cleanupDetect and remove legacy multi-server entries (--apply to commit).
uv run meta-data-mcp inspectLaunch mcp-inspector against the server.
uv run meta-data-mcp listInformational: list the internal plugins bundled in this server.
uv run meta-data-mcp infoInformational: show server overview. Pass --plugin for plugin-level details.
uv run meta-data-mcp versionPrint the package version.

The list command exists for transparency about what's bundled — plugins are not separately installable, runnable, or addressable. They are loaded automatically when the server starts.

Server tools (what the LLM calls)

Once meta-data-mcp is running, the LLM has access to two layers of tools — and you don't need to mention either to the user:

  1. Meta tools — the 13 server-level tools below. They make routing transparent: the LLM uses them to find, activate, and (if needed) create the right plugin without you telling it which tool to call.
  2. Plugin tools — ~330 tools coming from the 90 bundled plugins. In the default discovery-only mode they are activated per provider at runtime (or preloaded via META_DATA_MCP_PRELOAD). The LLM picks one after consulting the meta tools.
Meta tools
ToolPurpose
opendata_providers_findFree-text search over the plugin registry. Returns ranked matches. When nothing matches the response carries a no_match: true flag and a next_step hint pointing at opendata_plugins_draft + opendata_plugins_create.
opendata_explain_choiceShow the scoring breakdown for a search (useful for debugging routing decisions).
opendata_domains_listEnumerate the controlled domain vocabulary (health, legal, finance, earth-science, …).
opendata_regions_listEnumerate the controlled region vocabulary (us, eu, uk, global, …).
opendata_providers_describeFull metadata for one plugin by id — title, description, domains, regions, keywords, homepage, required env vars.
opendata_providers_listPaginated dump of the whole registry.
opendata_providers_activateActivate one provider so its tools become callable in this session.
opendata_providers_deactivateRemove an activated provider's tools from the current session catalog.
opendata_providers_list_activeList currently active providers and the tool names each contributes.
opendata_health_snapshotReturn per-provider health scores used by discovery health badges and routing context.
opendata_plugins_draftBuild a validated plugin YAML spec from structured inputs. Takes id, base_url, tool definitions (name, endpoint, params), and registry metadata. Validates id/tool-name casing, path-placeholder/param consistency, and parameter types, then emits a YAML string ready to feed into opendata_plugins_create. Use this so the LLM never has to hand-author YAML.
opendata_plugins_createAutonomously create a new plugin. Takes a YAML spec (typically produced by opendata_plugins_draft), runs the generator, imports the new module, registers it in the live registry, and hot-loads its tools onto the running server. Use this when opendata_providers_find returns no match.
opendata_tool_callProxy-call an activated plugin tool by name for environments that cannot directly invoke dynamically added tools.
The autonomous discovery flow

The reason this server is called "meta" is that it routes data requests on the user's behalf — including by *creating* the route when one doesn't exist yet. The full flow:

  1. User asks for data, e.g. "show me the most recent published CVEs."
  2. LLM calls `opendata_providers_find` with the query (cve, vulnerability, …).
  3. If the registry has a match: the LLM activates the matching provider (opendata_providers_activate, or activate_top in find) and then calls the plugin tool.
  4. If the registry has no match: the response includes no_match: true and a next_step field that explains the autonomous creation path. The LLM:
  5. Tells the user it's about to add coverage for this data source.
  6. Web-searches for an open API that exposes the requested data (e.g. the NVD or CIRCL CVE API).
  7. Calls opendata_plugins_draft with the API's id, base URL, and structured tool definitions. The server validates the inputs (id casing, path-placeholder consistency, parameter types) and returns a YAML string.
  8. Passes that YAML to opendata_plugins_create. The server materializes the plugin module + tests, imports the module, registers a ProviderEntry in the in-memory dynamic registry, and merges the new tools into the running server's tool list.
  9. Calls the newly-available tool to answer the user's original question.
  10. User gets their answer — and the plugin remains available for the rest of the session.

The materialized plugin lives on disk (meta_data_mcp/providers/{id}.py + tests/providers/test_{id}.py); contributors can clean it up, add it to meta_data_mcp/registry.py as a static entry, and open a PR so it becomes part of every shipped install.

Plugin tools

Every bundled plugin contributes its own tools under the one server. Their names are unique kebab-case identifiers, often using a provider-specific prefix (e.g. usgs-eq-feed-significant-week, frankfurter-latest, wikipedia-fetch-summary). The LLM discovers them through opendata_providers_find/opendata_providers_describe, activates the provider when needed, and can inspect session state with opendata_providers_list_active.

Auto-contribution of created plugins

When opendata_plugins_create builds a new plugin, meta-data-mcp opens a pull request contributing it back to the project so others can use it — the catalogue grows from real usage.

  • Consent: if your MCP client supports elicitation, you'll get a yes/no prompt (default yes) before the PR is opened.
  • What's shared: only the three generated files (spec, provider module, test stub) on a contribute/plugin- branch. Your working tree is never touched.
  • Opt out: set META_DATA_MCP_AUTO_CONTRIBUTE=0.
  • Target repo: derived from your origin remote; override with META_DATA_MCP_CONTRIBUTE_REPO=owner/repo.
  • Requires the gh CLI authenticated with push access. Without it, the branch is committed locally and the response tells you how to finish the PR.

Presentation layer (MCP Apps)

v2.0 adds a visual layer on top of every tool result. Hosts that support the MCP Apps extension (Claude Desktop, MCP Inspector, others) render bound tool results inline as interactive panels in a sandboxed iframe instead of as JSON text. Hosts that don't speak MCP Apps fall back to the same JSON they always got — the binding is purely additive.

Each MCP-Apps-aware tool declares its panel via _meta.ui.resourceUri on the tool description. The host fetches the ui:// resource (HTML + bundled JS, single payload, no external requests besides explicitly-whitelisted CDNs) and dispatches bidirectional postMessage events between the iframe and itself.

Shape primitives — ui://meta-data-mcp/shape/ /v1

Three reusable bundles cover the common payload contracts. Any tool whose response matches one of these shapes binds to the corresponding primitive automatically and gets a rich renderer for free.

ShapeRendersPayload contract
timeseries/v1Line chart + auto-computed profile (min/max/mean/stddev/gap-count) via Plotly.{points: [{date, value, series?}], axes: {x, y}, annotations?}
geofeatures/v1Leaflet map + marker cluster (with density layer for high-cardinality outputs).`{features: GeoJSON[{lat, lon, attrs}], layers?, facets?}`
records/v1Faceted, sortable, paginated HTML table + per-column auto-profile (type inference, top-k, null rate, range).{rows: [...], schema?, default_facets?}
Custom apps — ui://meta-data-mcp/app/ /v1

Some data shapes don't fit a generic pri

Only the beginning is shown; read the rest in the repo

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