Compatible with every major AI agent and IDE
What is the Apideck MCP Server?
Connect Apideck to your AI agent to streamline how you interact with multiple SaaS platforms. By using Apideck's Unified APIs, your agent can communicate with various CRM providers and manage user integrations without writing custom code for every service.
What you can do
- Unified CRM Access — List and filter contacts across different CRM providers like Salesforce, HubSpot, or Pipedrive using the
list_crm_contactstool. - Vault Management — Create sessions for users to link their own accounts (
create_vault_session), list existing connections, and retrieve or delete specific service links. - API Proxying — Execute direct requests to downstream service endpoints using
execute_proxywhen you need specific functionality not covered by the unified schema. - Connection Auditing — Inspect the status and details of active integrations using
get_vault_connectionto ensure data flow is healthy.
How it works
- Subscribe to this server
- Provide your Apideck API Key, App ID, and Consumer ID
- Start querying your unified ecosystem from Claude, Cursor, or any MCP client
Who is this for?
- Developers — who want to interact with multiple APIs through a single, normalized interface directly from their IDE.
- Product Managers — who need to audit user connections and CRM data across different environments without manual API calls.
- Support Teams — who need to verify if a customer's integration is correctly configured in the Vault through natural language.
Built-in capabilities (6)
Create a Vault session
Delete a Vault connection
Execute a Proxy API request
Get a specific Vault connection
g., salesforce, hubspot) using the Unified CRM API. List CRM contacts from a unified integration
List Vault connections
Why CrewAI?
When paired with CrewAI, Apideck becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Apideck 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
Apideck in CrewAI
Apideck and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Apideck 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 Apideck in CrewAI
The Apideck 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 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
Apideck for CrewAI
Every tool call from CrewAI to the Apideck MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I fetch contacts from a specific CRM like Salesforce or HubSpot?
Yes. Use the list_crm_contacts tool and provide the service_id (e.g., 'salesforce') to retrieve unified contact data from that specific integration.
How do I allow my users to configure their own integrations?
You can use the create_vault_session tool to generate a secure session URL where users can manage their connections within the Apideck Vault.
What if I need to call an API endpoint that isn't part of the unified schema?
The execute_proxy tool allows you to make direct calls to any downstream service URL using the stored credentials for a specific service_id.
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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