Bring Knowledge Graph
to CrewAI
Learn how to connect Wikidata to CrewAI and start using 8 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Wikidata MCP Server?
Connect to Wikidata, the central storage for structured data of Wikimedia projects. This MCP server allows your AI agent to tap into millions of items, properties, and statements using both traditional SPARQL queries and modern vector-based semantic search.
What you can do
- Entity Retrieval — Fetch full data and statements for any Wikidata Item (e.g., Q42) using the
get_itemandget_item_statementstools. - Advanced Querying — Execute complex SPARQL queries against the Wikidata Query Service (WDQS) with
execute_sparqlto find relationships and patterns across the entire graph. - Semantic Search — Use
search_items_vectorandsearch_properties_vectorto find entities and properties based on meaning rather than just exact keywords. - Data Contribution — Update the knowledge graph by creating statements or setting descriptions with
create_statementandset_item_description(requires OAuth). - Similarity Analysis — Compare text strings against specific entities to get semantic similarity scores using
get_similarity_score.
How it works
- Subscribe to this server
- Provide your User Agent (required by Wikimedia policy)
- Optionally provide an OAuth 2.0 Access Token for write operations
- Start exploring the world's knowledge from your favorite AI client
Who is this for?
- Researchers & Academics — instantly verify facts, dates, and relationships across history, science, and culture.
- Data Scientists — extract structured datasets for analysis or training without leaving the chat interface.
- Developers — find entity IDs and property schemas to integrate into applications or automate data enrichment.
Built-in capabilities (8)
Requires OAuth 2.0 Access Token. Create a new statement for an Item
Use hint:Query hint:optimizer "None" if queries timeout. Execute a SPARQL query
g., Q42) via the Wikibase REST API. Retrieve a specific Wikidata Item
Retrieve statements for a Wikidata Item
Compute similarity between text and an entity
Hybrid vector/keyword search for Items
Hybrid vector/keyword search for Properties
Requires OAuth 2.0 Access Token. Set an Item description
Why CrewAI?
When paired with CrewAI, Wikidata becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Wikidata tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools
- —
CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the
mcpsparameter and agents auto-discover every available tool at runtime - —
Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Wikidata in CrewAI
Wikidata and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Wikidata to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Wikidata in CrewAI
The Wikidata MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 8 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Wikidata for CrewAI
Every tool call from CrewAI to the Wikidata MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I find a Wikidata Item if I don't know its Q-ID?
You can use the search_items_vector tool. It performs a hybrid search using high-dimensional embeddings and keywords to find the most relevant entities based on your natural language description.
Is it possible to run complex queries like 'List all female scientists born in the 19th century'?
Yes, the execute_sparql tool allows you to run any valid SPARQL query against the Wikidata Query Service. This is the most powerful way to filter and aggregate data across the entire knowledge graph.
Can I use this server to update information on Wikidata?
Yes, if you provide an OAuth 2.0 Access Token, you can use create_statement to add new data or set_item_description to update descriptions in various languages.
How does CrewAI discover and connect to MCP tools?
CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
Can different agents in the same crew use different MCP servers?
Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
What happens when an MCP tool call fails during a crew run?
CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
Can CrewAI agents call multiple MCP tools in parallel?
CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
Can I run CrewAI crews on a schedule (cron)?
Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.
MCP tools not discovered
Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
Agent not using tools
Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
Timeout errors
CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
Rate limiting or 429 errors
Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.
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