Bring Documentation
to CrewAI
Learn how to connect Wiki.js to CrewAI and start using 6 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 Wiki.js MCP Server?
Connect your Wiki.js instance to any AI agent and take full control of your internal knowledge base through natural conversation. This server allows you to interact with your documentation without leaving your chat interface.
What you can do
- Page Management — Create new pages with full metadata, update existing content by ID, or delete outdated documentation.
- Search & Discovery — Search across your entire wiki for specific keywords or list all available pages to understand your knowledge structure.
- Content Retrieval — Fetch the raw content and metadata of any page using its URL path and locale.
- Flexible Editing — Support for different editor types and publishing statuses (published/private) directly via the API.
How it works
- Subscribe to this server
- Enter your Wiki.js API URL and API Key
- Start managing your documentation from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Developers — quickly update technical docs or search for internal guides while coding.
- Knowledge Managers — organize and prune wiki content through simple natural language commands.
- Support Teams — find relevant internal documentation to answer customer queries faster.
Built-in capabilities (6)
Create a new Wiki.js page
Delete a Wiki.js page
Fetch a Wiki.js page by path
List all Wiki.js pages
Search for content in Wiki.js
Update an existing Wiki.js page
Why CrewAI?
When paired with CrewAI, Wiki.js becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Wiki.js 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
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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
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Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Wiki.js in CrewAI
Wiki.js and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Wiki.js 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 Wiki.js in CrewAI
The Wiki.js 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 6 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
Wiki.js for CrewAI
Every tool call from CrewAI to the Wiki.js MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I search for specific keywords across all my wiki pages?
Yes! Use the search_pages tool with your query string. The agent will scan all content and return relevant page matches including titles and paths.
How do I fetch the content of a specific page if I have the URL path?
Use the get_page tool. Simply provide the path (e.g., 'home' or 'engineering/setup') and the agent will retrieve the full content and metadata for that specific page.
Is it possible to modify an existing page's content?
Absolutely. Use the update_page tool by providing the unique page ID and the new content or title you wish to apply. The agent will handle the update via the Wiki.js API.
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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