Skip to main content

MCP Wikidata Server

Project description

Wikidata MCP Server

A server implementation for Wikidata API using the Model Context Protocol (MCP). This project provides tools to interact with Wikidata, such as searching identifiers (entity and property), extracting metadata (label and description) and executing sparql query.


Installation

Install uv if it is not installed yet.

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

Then, install dependencies.

$ git clone https://github.com/zzaebok/mcp-wikidata.git
$ cd mcp-wikidata
$ uv sync
# if you want to run client example together
$ uv sync --extra example

Run

Run the server with:

$ uv run src/server.py

If you want to test it with a simple client code (with langchain-mcp-adapters), run the client with:

# in another shell
$ uv run src/client.py

The LLM extracts valid entity and property identifiers, executes a sparql query, and finally recommend a movie directed by Bong Joon-ho.

See the execution output
{
  "messages": [
      HumanMessage(
          content="Can you recommend me a movie directed by Bong Joonho?",
      ),
      AIMessage(
          tool_calls=[
              {
                  "name": "search_entity",
                  "args": {"query": "Bong Joon-ho"},
              }
          ],
      ),
      ToolMessage(
          content="Q495980",
          name="search_entity",
      ),
      AIMessage(
          tool_calls=[
              {
                  "name": "get_properties",
                  "args": {"entity_id": "Q495980"},
              }
          ],
      ),
      ToolMessage(
          content='["P345", "P244", "P214", "P227", ...]',
          name="get_properties",
      ),
      AIMessage(
          tool_calls=[
              {
                  "name": "search_property",
                  "args": {"query": "director"},
              }
          ],
      ),
      ToolMessage(
          content="P57",
          name="search_property",
      ),
      AIMessage(
          tool_calls=[
              {
                  "name": "execute_sparql",
                  "args": {
                      "sparql_query": 'SELECT ?film ?filmLabel WHERE {\n  ?film wdt:P57 wd:Q495980.\n  SERVICE wikibase:label { bd:serviceParam wikibase:language "en". }\n} LIMIT 1'
                  },
              }
          ],
      ),
      ToolMessage(
          content='[{"film": {"type": "uri", "value": "http://www.wikidata.org/entity/Q483761"}, "filmLabel": {"xml:lang": "en", "type": "literal", "value": "Mother"}}]',
          name="execute_sparql",
      ),
      AIMessage(
          content='I recommend the movie "Mother," which was directed by Bong Joon-ho.',
      ),
  ]
}

Wikidata MCP Tools

The following tools are implemented in the server:

Tool Description
search_entity(query: str) Search for a Wikidata entity ID by its query.
search_property(query: str) Search for a Wikidata property ID by its query.
get_properties(entity_id: str) Get the properties associated with a given Wikidata entity ID.
execute_sparql(sparql_query: str) Execute a SPARQL query on Wikidata.
get_metadata(entity_id: str, language: str = "en") Retrieve the English label and description for a given Wikidata entity ID.

License

MIT License

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mseep_mcp_wikidata-0.1.0.tar.gz (3.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mseep_mcp_wikidata-0.1.0-py3-none-any.whl (3.4 kB view details)

Uploaded Python 3

File details

Details for the file mseep_mcp_wikidata-0.1.0.tar.gz.

File metadata

  • Download URL: mseep_mcp_wikidata-0.1.0.tar.gz
  • Upload date:
  • Size: 3.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.12

File hashes

Hashes for mseep_mcp_wikidata-0.1.0.tar.gz
Algorithm Hash digest
SHA256 dbc2893d2f712cbe977820d41e12c888057c7391ac00de0d56dfff590dc7c878
MD5 531ce25d58e470ac7c319c94a832683a
BLAKE2b-256 89f7f1609f5806695d47681660fc9ca5cbc5d7b36cbbd7e424c3a7a34a6d6079

See more details on using hashes here.

File details

Details for the file mseep_mcp_wikidata-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for mseep_mcp_wikidata-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 6a52e5d23f9b1c71c4d48285e877f0a7b346c01456900875d94c803b489d8709
MD5 f0b5d603f29a3a224dae33283ed1c3fc
BLAKE2b-256 129a1dcae682bffeab7de938e3e93d011faab31618d5ed30c506becb0e5f7b05

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page