Bring Knowledge Base
to LlamaIndex
Create your Vinkius account to connect Mem AI (Knowledge Workspace) to LlamaIndex and start using all 12 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Mem AI (Knowledge Workspace) MCP Server?
Connect your Mem.ai workspace to any AI agent and take full control of your personal and team knowledge through natural conversation.
What you can do
- Knowledge Orchestration — Create new mems (notes) using Markdown directly from your agent, instantly transforming textual ideas into indexed knowledge vectors
- AI Semantic Search — Leverage dense semantic similarity to find notes across your entire workspace, identifying relevant information based on meaning rather than explicit keywords
- Deep Content Retrieval — Extract the full scalar text body and context metadata for specific mems to retrieve precise project details securely
- Collection Management — Establish thematic groupings (Collections) and attach live mems structurally to maintain organized project boundaries natively
- Quick Capture (Mem It) — Trigger rapid capture blocks for links, snippets, or raw thoughts, allowing your agent to log ideas without manual dashboard navigation
- Contextual Updates — Mutate existing mem content to keep project logs and meeting notes up-to-date while preserving historical knowledge mappings
- Resource Inventory — List all available mems or explore specific collections to understand your knowledge distribution and team documentation footprint
How it works
- Subscribe to this server
- Enter your Mem.ai API Key
- Start managing your workspace from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Knowledge Workers — organize research and meeting notes through natural conversation without manual outliner management
- Project Teams — sync project documentation and manage shared knowledge collections directly from your workspace
- Researchers — leverage AI semantic search to bridge ideas and retrieve relevant context across massive personal knowledge bases efficiently
Built-in capabilities (12)
Attach live Mems structurally inside explicitly mapped Collections
Establish new logical thematic groupings mapping notes
ai. Converts plain textual knowledge to indexed vectors immediately mapped implicitly via AI. Create a new mem (note) in Mem.ai using Markdown
No recovery is possible via API. Irreversibly vaporize a mem document globally
Inspect specific Collection metadata elements
Retrieve explicit full context metadata by target Mem ID
Query ALL explicit Mem bodies inside specific Collections
Query explicitly tracked thematic Collections arrays
Returns identifiers and raw bodies. Careful, this returns heavy payloads. List all raw mems across the global workspace
Quick capture shortcut generating automated blocks
AI semantic search looking into all indexed knowledge
Replaces absolute text values so ensure `get_mem` was run to append rather than destroy inadvertently. Update pre-existing mem content natively swapping strings
Why LlamaIndex?
LlamaIndex agents combine Mem AI (Knowledge Workspace) tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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 Mem AI (Knowledge Workspace) tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Mem AI (Knowledge Workspace) tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Mem AI (Knowledge Workspace), a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Mem AI (Knowledge Workspace) tools were called, what data was returned, and how it influenced the final answer
Mem AI (Knowledge Workspace) in LlamaIndex
Why run Mem AI (Knowledge Workspace) with Vinkius?
The Mem AI (Knowledge Workspace) connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 12 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect Mem AI (Knowledge Workspace) using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Mem AI (Knowledge Workspace) and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Mem AI (Knowledge Workspace) to LlamaIndex through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
Mem AI (Knowledge Workspace) for LlamaIndex
Every request between LlamaIndex and Mem AI (Knowledge Workspace) is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
How is Mem's AI search different from regular keyword search?
Mem uses semantic similarity. When your agent uses the search_mems tool, it identifies notes based on the meaning of your query. This means you can find relevant context even if you don't remember the exact words used in the original note.
Can I organize my notes into folders using my agent?
In Mem, folders are called 'Collections'. Use the create_collection and add_mem_to_collection tools. Your agent can establish thematic groups and link specific mems to them structurally, maintaining an organized workspace through conversation.
What is the 'Mem It' tool used for?
The mem_it tool is a quick capture shortcut. Your agent can use it to instantly log raw thoughts, URLs, or snippets into your workspace with automated formatting, perfect for high-speed idea tracking during your workflow.
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 Mem AI (Knowledge Workspace) 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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