Compatible with every major AI agent and IDE
What is the Activepieces MCP Server?
Connect your Activepieces account to any AI agent to orchestrate complex automations and monitor your business workflows through natural language.
What you can do
- Flow Management — List, create, retrieve, and delete automation flows within your projects using
list_flowsandcreate_flow. - Execution Monitoring — Track flow runs, check statuses, and inspect detailed step results for debugging with
list_flow_runsandget_flow_run. - App Connections — Manage credentials and connections for external services like Slack, Discord, or Google Sheets via
list_app_connections. - Flow Operations — Apply structural changes or status updates to existing flows programmatically using
apply_flow_operation. - Organization — List and manage folders to keep your automation workspace tidy with
list_folders.
How it works
- Subscribe to this server
- Enter your Activepieces API Key
- Start orchestrating your automations from Claude, Cursor, or any MCP-compatible client
No more manual checking of execution logs or switching tabs to enable/disable flows. Your AI acts as a dedicated automation engineer.
Who is this for?
- DevOps & Automation Engineers — monitor flow health and trigger updates directly from the terminal or chat.
- Product Operations — manage app connections and verify data consistency across automated workflows.
- Marketing Teams — check the status of lead-gen flows and ensure integrations are running smoothly.
Built-in capabilities (32)
Add a custom piece to the platform
g., MOVE_ACTION, CHANGE_STATUS). Apply an operation to a flow
Configure Git sync for a project
Create a new flow
Create a new folder
Create a new project
Create a project release
Delete an app connection
Delete a flow by ID
Delete a folder
Delete a global connection
Remove a member from a project
Get a specific flow by ID
Get detailed execution data for a flow run
Get MCP server configuration for AI assistants
Invite a user to the platform or project
List app connections
List flow runs
List automation flows
List folders
List global connections
List members of a project
List projects
List records in a table
List internal data tables
List users
Rotate MCP token for a project
Update a folder name
Update project settings
Update a specific record
Supports SECRET_TEXT, OAUTH2, BASIC_AUTH, CUSTOM_AUTH, etc. Create or update an app connection
Create or update a global connection
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Activepieces through native MCP adapters. Connect 32 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
- —
The largest ecosystem of integrations, chains, and agents. combine Activepieces MCP tools with 500+ LangChain components
- —
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
- —
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
- —
Memory and conversation persistence let agents maintain context across Activepieces queries for multi-turn workflows
Activepieces in LangChain
Activepieces and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Activepieces to LangChain 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 Activepieces in LangChain
The Activepieces 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 32 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LangChain 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
Activepieces for LangChain
Every tool call from LangChain to the Activepieces MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I check why a specific flow execution failed?
Yes. Use the get_flow_run tool with the Run ID to retrieve detailed execution data, including step results and error messages.
How do I update the status of an existing flow?
You can use the apply_flow_operation tool. It allows you to send an operation payload to change the flow's status or modify its structure.
Can I see which external apps are connected to my project?
Yes, the list_app_connections tool retrieves all credentials and connections configured for a specific Project ID.
How does LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters
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