
Meta Data Mcp
io.github.derekslinz由 GitHub 账号 derekslinz 发布v2.5.0更新于 Oct 24, 2026
Query 76 open data APIs — government, science, finance, environment, and more.
概览
一个本地 MCP 服务器,把助手的数据问题路由到约 90 个内置开放数据 API,涵盖政府统计、科学、金融、环境等。
- 可以做什么
- 在内部注册表中查找、描述、列出并激活开放数据提供方,支持领域与地区词表以及健康评分,用于路由决策和调试检索打分。调用内置插件提供的约 330 个工具,例如汇率、地震、CVE 记录、临床试验、天气和生物多样性观测。在没有匹配提供方时,根据结构化输入起草并创建新插件,并在本次会话中热加载其工具。为每个结果返回引用清单,列出上游 URL、状态、抓取时间和许可,可选提供防篡改摘要。在支持的宿主中以交互面板(图表、地图、表格、关系图)呈现结果。
- 适用场景
- 当你希望一次安装就能回答跨多个公共数据集(统计、健康、环境、金融、安全)的临时问题,并让助手自行发现合适的数据源,而不必为每个 API 单独配置服务器时使用。
- 运行要求
- 作为本地 Python 进程运行,通过 uv 从 PyPI 包安装;setup 命令会向检测到的 MCP 客户端配置写入条目,并先做备份。可选 API 密钥用于提高速率限制:COURTLISTENER_API_TOKEN、NVD_API_KEY、OPENAQ_API_KEY、OPENSANCTIONS_API_KEY、UN_COMTRADE_API_KEY,以及用于礼貌池 User-Agent 的 META_DATA_MCP_CONTACT。需要访问上游 API 的网络。
安装
在 SourceWeft 中
- 打开 控制台中的 Meta Data Mcp,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
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).
Then register the server with every MCP client installed on your machine:
The command auto-detects which MCP clients you have installed and adds one meta-data-mcp entry under mcpServers in each. Supported clients:
Each existing config is backed up to <file>.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:
Target a single client (or write to every supported client regardless of detection):
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):
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.
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:
- 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.
- 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
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:
- User asks for data, e.g. "show me the most recent published CVEs."
- LLM calls
opendata_providers_findwith the query (cve,vulnerability, …). - If the registry has a match: the LLM activates the matching provider (
opendata_providers_activate, oractivate_topin find) and then calls the plugin tool. - If the registry has no match: the response includes
no_match: trueand anext_stepfield that explains the autonomous creation path. The LLM:- Tells the user it's about to add coverage for this data source.
- Web-searches for an open API that exposes the requested data (e.g. the NVD or CIRCL CVE API).
- Calls
opendata_plugins_draftwith 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. - Passes that YAML to
opendata_plugins_create. The server materializes the plugin module + tests, imports the module, registers aProviderEntryin the in-memory dynamic registry, and merges the new tools into the running server's tool list. - Calls the newly-available tool to answer the user's original question.
- 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-<id>branch. Your working tree is never touched. - Opt out: set
META_DATA_MCP_AUTO_CONTRIBUTE=0. - Target repo: derived from your
originremote; override withMETA_DATA_MCP_CONTRIBUTE_REPO=owner/repo. - Requires the
ghCLI 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/<name>/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.
Custom apps — ui://meta-data-mcp/app/<name>/v1
Some data shapes don't fit a generic primitive. v2.0 ships dedicated apps for them:
Building new apps
Adding a UI binding to a generated provider is now a one-line spec change:
See tools/specs/README.md for the full reference. Bundle-size budgets are enforced in CI (warn ≥ 100 KB, error ≥ 1 MB); the v2.0 bundles range from 14 KB (timeseries primitive) to 34 KB (vulnerability app), all comfortably inside the budget.
Citable answers
Every tool result carries a machine-readable citation manifest: exactly which upstream requests produced it. The transport kernel records each HTTP exchange during a tool call, and the result's first content block gains a _meta["meta-data-mcp/citations"] entry:
This is what makes an LLM data answer auditable: the exact URL(s) — query parameters included — when they were fetched, whether they came from the transport cache, and the provider's license/attribution terms. Anyone can re-issue the URL and check the claim.
- Secrets never leak. Values of sensitive query parameters are replaced with
REDACTED— an exact denylist (api_key,token,appid, …) plus conservative heuristics (*key,*token,*secret*,*signature*, …) that also cover presigned cloud-storage URLs and plugin-specific key params. Userinfo credentials in the URL itself (https://user:pass@host) are redacted too; parameter names are preserved so the URL stays reproducible with your own credentials. Headers never enter the manifest. - Failed exchanges are cited too — a 4xx/5xx a handler recovered from, and the intermediate 429/5xx attempts the kernel's retry loop absorbed, are part of how the answer was produced; filter on
status. (A tool call that errors out returns the SDK'sisErrorresult, which carries no manifest.) - Honest timestamps.
fetched_atis when the bytes were actually fetched: cache-served exchanges report the original fetch time withcache_hit: true, not the cache-read time. - On by default. Set
META_DATA_MCP_CITATIONS=0to disable. Complements the opt-in tamper-evidence digest (META_DATA_MCP_PROVENANCE); both can coexist on the same result.
Bundled plugins (90)
This is what's inside the one server. You don't install these individually — they all come along.
Government / Civic
Statistics / Economics
Finance / Markets
Health & Life Sciences
Earth Science / Weather / Environment
Biodiversity / Space / Physics
Geo / Mapping / Knowledge
Agriculture / Trade
Security / Vulnerability
Transit / Aviation
Scholarly Literature
Culture / Books
News / Media
Networking / Internet
Legal
Optional environment variables
A few bundled plugins accept optional API keys for higher rate limits. Set these in your shell or in the Claude Desktop server config's env block:
Server runtime flags
Transports
run defaults to SSE (HTTP, port 8000) so you can connect from the MCP Inspector or remote clients. For Claude Desktop (which the setup command targets), the spawned process uses stdio:
Roadmap
Shipped
- Hierarchical discovery (v2.0):
opendata_providers_findwith ranked scoring replaces the originally-planned browse/list tools. - Agent-driven generation (v2.1):
opendata_plugins_draft+opendata_plugins_createlet the model close coverage gaps autonomously. Hardened in v2.1.1 with input allowlists, path containment, and a post-generation AST validator (14 RCE/path-traversal/bypass paths closed). - Self-hosted SSE deployment (v2.1): bearer-auth-protected, systemd-managed, reverse-proxied.
- Multi-language SDK (v2.2): Python embedded client (
meta_data_mcp.sdk) and TypeScript/Node client (@meta-data-mcp/sdk) for discovery over MCP SSE. - OAuth 2.0 (v2.3): Authorization Code + PKCE + Dynamic Client Registration. Works with Claude.ai (StreamableHTTP) and MCP Inspector.
/.well-known/oauth-authorization-server,/.well-known/oauth-protected-resource, and/.well-known/openid-configurationall served. - MCP registry provider (v2.3.4):
mcp_registry_searchandmcp_registry_list— discover other MCP servers from within meta-data-mcp. Listed on the official MCP registry and Smithery.
Still ahead
- Expand provider coverage beyond the current 90.
Credits
- Originally conceived by grll as
opendata-mcp. - Forked and reshaped around the single-server "meta-mcp" model.
- Built on Anthropic's open-source MCP spec.
License
MIT — see LICENSE.
来源:README.md,提交 cae17f2
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0版本历史
1- v2.5.0最新Sep 16, 2026
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