Bring Rag Framework
to CrewAI
Create your Vinkius account to connect Cognita (RAG Framework) to CrewAI and start using all 7 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 Cognita (RAG Framework) MCP Server?
Connect your Cognita (TrueFoundry) instance to any AI agent and take full control of your modular RAG workflows through natural conversation.
What you can do
- Knowledge Collections — List and audit RAG collections to inspect embedding configurations, token lengths, and parser details
- Data Ingestion — Force sync remote files from SQL, Cloud Storage, or APIs into your vector space to update your knowledge base
- RAG Queries — Dispatch automated AI questions that query your vector store and synthesize accurate answers from stored context
- Chunk Auditing — Perform lexical or semantic searches to pull raw document chunks and verify precise text segments
- Model Registry — Enumerate available LLMs and embedding models registered inside your modular Cognita installation
- DataSource Management — List all connected data sources to verify which external data is mapped into your AI workflows
How it works
- Subscribe to this server
- Enter your Cognita Base URL and API Key (if required by your TrueFoundry or self-hosted setup)
- Start managing your RAG pipelines from Claude, Cursor, or any MCP-compatible client
Who is this for?
- AI Engineers — test and debug RAG queries and chunk retrieval logic without writing Python scripts
- Data Scientists — monitor ingestion pipelines and verify document chunking consistency across collections
- Product Teams — quickly audit what knowledge is being fed to AI agents during the prototyping phase
- DevOps Teams — monitor Cognita model registries and ensure that all LLM endpoints are active and reachable
Built-in capabilities (7)
Retrieve explicit Cloud logging tracing explicit Payload IDs
Provision a highly-available JSON Payload generating new Resource directories
Identify bounded routing spaces inside the Headless Cognita RAG limit
Perform structural extraction of properties driving active Buckets
Inspect deep internal arrays mitigating specific Picture constraints
Identify precise active arrays spanning rented Transformation vectors
Enumerate explicitly attached structured rules exporting active Presets
Why CrewAI?
When paired with CrewAI, Cognita (RAG Framework) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Cognita (RAG Framework) 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
Cognita (RAG Framework) in CrewAI
Why run Cognita (RAG Framework) with Vinkius?
The Cognita (RAG Framework) 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 7 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 Cognita (RAG Framework) using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Cognita (RAG Framework) and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Cognita (RAG Framework) to CrewAI 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
Cognita (RAG Framework) for CrewAI
Every request between CrewAI and Cognita (RAG Framework) 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
Can my agent perform semantic RAG queries against my collections?
Yes. The 'rag_query' tool allows you to ask questions in natural language. The agent queries your vector store via Cognita and uses an LLM to synthesize a final answer based explicitly on the retrieved context.
How can I trigger a data ingestion pipeline through the agent?
Provide the collection name and the data source FQN (Fully Qualified Name). The 'ingest_data' tool will command the Cognita backend to start a sync, updating your RAG vector space with the latest remote documents.
Can I audit the raw document chunks before LLM generation?
Absolutely. Use the 'search_chunks' tool to perform vector searches that return raw text segments and metadata without LLM synthesis. This is the perfect way to verify that your retrieval logic is pulling the correct data boundaries.
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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