Why do I get an error when providing my token?

Tettra's API keys are exclusively available to workspaces on their **Scaling** or **Professional** subscription tiers. If your team operates on a free or basic plan, the API credentials menu will not be accessible and requests will be blocked.

Can the AI rewrite existing company wiki articles?

Yes. Using the `update_wiki_page` function, the AI can overwrite existing body content and titles. It adopts your user profile's access permissions, meaning it can only update pages you personally have edit rights for in the Tettra UI.

Where do I track down my Tettra Team ID?

Your Team ID is the slug prefix used in your Tettra domain. For example, if you access your wiki primarily through `https://app.tettra.co/teams/acme-corp`, your Team ID is exactly `acme-corp`.

Tettra MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Tettra
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Tettra through Vinkius, pass the Edge URL in the `mcps` parameter and every Tettra tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Tettra Specialist",
    goal="Help users interact with Tettra effectively",
    backstory=(
        "You are an expert at leveraging Tettra tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Tettra "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

About Tettra MCP Server

Connect your Tettra internal knowledge base to any AI agent and bring your company's documentation directly into your developer workflow. No more switching tabs to look up API specs or onboarding guides.

When paired with CrewAI, Tettra becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Tettra tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Deep Search — Perform full-text searches across all your company's Tettra pages to instantly find answers and organizational knowledge
Knowledge Retrieval — Read the complete markdown/HTML content of any page, technical guide, or team policy natively inside your chat
Content Creation — Command your agent to draft and publish new wiki pages, or suggest documentation updates on the fly
Category Navigation — Browse through your team's top-level categories, root folders, and subcategories visually
Q&A Management — Post new questions to your team's internal Q&A board or list unanswered questions right from your IDE

The Tettra MCP Server exposes 12 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Tettra to CrewAI via MCP

Follow these steps to integrate the Tettra MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from Tettra

Why Use CrewAI with the Tettra MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Tettra through the Model Context Protocol.

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 `mcps` parameter 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

Tettra + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Tettra MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Tettra for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Tettra, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Tettra tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Tettra against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Tettra MCP Tools for CrewAI (12)

These 12 tools become available when you connect Tettra to CrewAI via MCP:

create_qa_question

Posts a new question in the Tettra Q&A system

create_wiki_page

Provide title, content, and category ID. Creates a new wiki page in a specific category

get_category_details

Retrieves details for a specific Tettra category

get_page_content

Returns title and Markdown/HTML body. Retrieves the full content and metadata of a specific Tettra page

list_categories

Lists all top-level categories in the Tettra wiki

list_pages_in_category

Lists all wiki pages within a specific category

list_qa_questions

Lists all questions posted in the Tettra Q&A system

list_subcategories

Lists all subcategories under a specific parent category

search_pages

Returns up to 5 matching pages. Full-text search across all Tettra wiki pages

suggest_new_page

Suggests a new wiki page to the team

update_wiki_page

Provide the page ID and the new fields. Updates the title or content of an existing Tettra page

verify_wiki_page

Marks a Tettra page as verified and up-to-date

Example Prompts for Tettra in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Tettra immediately.

"Search the wiki for 'Database Migration Checklist'."

"Create a new wiki page in the 'Support' category explaining how to handle refund requests."

"Mark page ID 883 as verified and up to date."

Troubleshooting Tettra MCP Server with CrewAI

Common issues when connecting Tettra to CrewAI through the Vinkius, and how to resolve them.

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.

Tettra + CrewAI FAQ

Common questions about integrating Tettra MCP Server with CrewAI.

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.