Compatible with every major AI agent and IDE
What is the Tome (AI Storytelling) MCP Server?
Connect your Tome account to any AI agent to streamline your AI-driven storytelling and presentation workflows through natural conversation.
What you can do
- Workspaces & Tomes — List all accessible workspaces and fetch active tomes directly from the Tome cloud
- Tome Management — Create new tomes in specific workspaces and organize your storytelling projects
- Page Operations — Add new pages to existing tomes to expand your narrative dynamically
- Deep Inspection — Fetch complete metadata and page details for specific tomes to understand their structure
How it works
- Subscribe to this server
- Enter your Tome API Key
- Start generating presentations from Claude, Cursor, or any MCP-compatible client
No more manual slide creation. Your AI acts as a creative director, building out your vision page by page.
Who is this for?
- Content Creators — instantly scaffold stories and presentations without leaving your AI chat
- Marketing Teams — manage workspace assets and create new campaign decks via automation
- Product Managers — document features and roadmaps by generating tomes directly from project specs
Built-in capabilities (5)
Add a new page to an existing tome
Create a new tome in a workspace
Get detailed information about a specific tome
List tomes in a workspace
List Tome workspaces
Why CrewAI?
When paired with CrewAI, Tome (AI Storytelling) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Tome (AI Storytelling) 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
- —
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
- —
Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports
Tome (AI Storytelling) in CrewAI
Tome (AI Storytelling) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Tome (AI Storytelling) 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 Tome (AI Storytelling) in CrewAI
The Tome (AI Storytelling) 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 5 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
Tome (AI Storytelling) for CrewAI
Every tool call from CrewAI to the Tome (AI Storytelling) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I see the full structure of a specific presentation including its pages?
Yes! Use the get_tome tool with the specific Tome ID. Your agent will retrieve detailed information about the tome, including its page list and metadata.
How do I add a new slide or page to an existing project?
Simply use the add_page action. Provide the tome_id and the title for your new page, and the agent will insert it into your presentation immediately.
Can I list all the presentations I have in a specific workspace?
Yes, use the list_tomes tool. By providing the workspace_id, the agent will return a list of all tomes available in that specific environment.
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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