Bring Documentation
to LlamaIndex
Learn how to connect Wiki.js to LlamaIndex 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- Page Management — Create new pages with full metadata, update existing content by ID, or delete outdated documentation.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 LlamaIndex?
LlamaIndex agents combine Wiki.js tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine Wiki.js tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Wiki.js tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Wiki.js, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Wiki.js tools were called, what data was returned, and how it influenced the final answer
Wiki.js in LlamaIndex
Wiki.js and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Wiki.js to LlamaIndex 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 LlamaIndex
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 LlamaIndex 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 LlamaIndex
Every tool call from LlamaIndex 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 LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query Wiki.js tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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