Bring Feature Flags
to LangChain
Learn how to connect Statsig to LangChain and start using 12 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Statsig MCP Server?
Connect your Statsig project to any AI agent to manage feature rollouts and product experiments through natural conversation.
What you can do
- Feature Gates — Evaluate if a feature is enabled for a specific user or list all project gates
- Dynamic Configs — Fetch JSON configurations and experiments to control app behavior without code changes
- Event Logging — Log custom events for real-time analytics and metric calculation
- Gate Management — Create, update, or delete feature gates directly via the Console API
- Layer Inspection — Evaluate layers and retrieve parameter values for specific users
How it works
- Subscribe to this server
- Enter your Statsig Server Secret Key (for evaluation) and Console API Key (for management)
- Start managing your product experiments from Claude, Cursor, or any MCP client
Who is this for?
- Product Managers — check gate statuses and create new feature flags without leaving the chat
- Developers — verify evaluation logic and log test events directly from the IDE
- Data Scientists — inspect experiment configurations and verify metric logging
Built-in capabilities (12)
Requires STATSIG_SERVER_SECRET_KEY. Evaluates one or more feature gates for a user
Requires STATSIG_CONSOLE_API_KEY. Create a new dynamic config
Requires STATSIG_CONSOLE_API_KEY. Create a new feature gate
Requires STATSIG_CONSOLE_API_KEY. Delete a feature gate
Requires STATSIG_SERVER_SECRET_KEY. Fetches configuration values for a dynamic config or experiment
Requires STATSIG_CONSOLE_API_KEY. Read a specific dynamic config
Requires STATSIG_CONSOLE_API_KEY. Read a specific feature gate
Requires STATSIG_SERVER_SECRET_KEY. Fetches parameter values from a layer
Requires STATSIG_CONSOLE_API_KEY. List all dynamic configs in the project
Requires STATSIG_CONSOLE_API_KEY. List all feature gates in the project
Requires STATSIG_SERVER_SECRET_KEY. Logs custom events for analytics and metric calculation
Requires STATSIG_CONSOLE_API_KEY. Update an existing feature gate
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Statsig through native MCP adapters. Connect 12 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.
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The largest ecosystem of integrations, chains, and agents. combine Statsig MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Statsig queries for multi-turn workflows
Statsig in LangChain
Statsig and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Statsig 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 Statsig in LangChain
The Statsig 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 12 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
Statsig for LangChain
Every tool call from LangChain to the Statsig MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
What is the difference between the Server Secret Key and the Console API Key?
The Server Secret Key is used for evaluation tools like check_gate and get_config. The Console API Key is required for management actions like list_gates or create_gate.
How do I evaluate a gate for a specific user?
Use the check_gate tool. You must provide the gateName and a user JSON object containing at least a userID (e.g., {"userID": "123"}).
Can I log custom events for analytics?
Yes, use the log_event tool to send an array of event objects including name, value, and user metadata to Statsig for real-time metric calculation.
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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