
Postman MCP Server
The Postman MCP Server enables AI assistants to execute Postman collections and automate API testing workflows using Newman, all via a standardized MCP interfac...
Seamlessly integrate PostHog analytics, feature flag management, and error tracking into your FlowHunt AI workflows with the PostHog MCP Server.
The PostHog MCP (Model Context Protocol) Server is designed to connect AI assistants with the PostHog analytics platform, enabling enhanced development and operational workflows. By acting as a bridge between AI clients and PostHog’s feature flag management, analytics, and error tracking capabilities, the server allows AI models to perform tasks such as querying active feature flags, managing feature toggles, and retrieving error data. This integration empowers developers and teams to interact with their analytics data, control feature rollouts, and troubleshoot issues programmatically via LLMs, streamlining product management and observability processes.
{
"mcpServers": {
"posthog": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://mcp.posthog.com/sse",
"--header",
"Authorization:${POSTHOG_AUTH_HEADER}"
],
"env": {
"POSTHOG_AUTH_HEADER": "Bearer {INSERT_YOUR_PERSONAL_API_KEY_HERE}"
}
}
}
}
{
"mcpServers": {
"posthog": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://mcp.posthog.com/sse",
"--header",
"Authorization:${POSTHOG_AUTH_HEADER}"
],
"env": {
"POSTHOG_AUTH_HEADER": "Bearer {INSERT_YOUR_PERSONAL_API_KEY_HERE}"
}
}
}
}
{
"mcpServers": {
"posthog": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://mcp.posthog.com/sse",
"--header",
"Authorization:${POSTHOG_AUTH_HEADER}"
],
"env": {
"POSTHOG_AUTH_HEADER": "Bearer {INSERT_YOUR_PERSONAL_API_KEY_HERE}"
}
}
}
}
{
"mcpServers": {
"posthog": {
"command": "npx",
"args": [
"-y",
"mcp-remote@latest",
"https://mcp.posthog.com/sse",
"--header",
"Authorization:${POSTHOG_AUTH_HEADER}"
],
"env": {
"POSTHOG_AUTH_HEADER": "Bearer {INSERT_YOUR_PERSONAL_API_KEY_HERE}"
}
}
}
}
Securing API Keys
Always store API keys as environment variables, not in plain text. Example:
"env": {
"POSTHOG_AUTH_HEADER": "Bearer {INSERT_YOUR_PERSONAL_API_KEY_HERE}"
}
Using MCP in FlowHunt
To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:
Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:
{
"MCP-name": {
"transport": "streamable_http",
"url": "https://yourmcpserver.example/pathtothemcp/url"
}
}
Once configured, the AI agent is able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “MCP-name” to “posthog” and replace the URL with your own MCP server URL.
Section | Availability | Details/Notes |
---|---|---|
Overview | ✅ | |
List of Prompts | ✅ | Details from README.md |
List of Resources | ⛔ | Not documented |
List of Tools | ✅ | docs-search (available if Inkeep API key is set) |
Securing API Keys | ✅ | Documented in setup instructions |
Sampling Support (less important in evaluation) | ⛔ | Not documented |
Based on the available information, the PostHog MCP Server is easy to set up and well-documented for prompts and tools, but is limited in explicit resource and advanced MCP feature documentation. It scores well for basic integration and developer utility.
Has a LICENSE | ✅ (MIT) |
---|---|
Has at least one tool | ✅ |
Number of Forks | 3 |
Number of Stars | 35 |
The PostHog MCP Server connects AI assistants to the PostHog analytics platform, enabling direct access to feature flag management, analytics, and error tracking via the Model Context Protocol.
You can query feature flags, create or manage toggles, retrieve error analytics, and gain operational insights—all programmatically, from within your FlowHunt AI workflows.
Yes, you should always store your PostHog API key as an environment variable, not in plain text. The setup guides show you how to do this for each supported client.
Yes, the server supports the docs-search tool (if configured with an Inkeep API key), allowing AI agents to search documentation for troubleshooting and onboarding.
Basic setup requires only your API key and the provided JSON configuration. Advanced resource documentation is not required for standard integrations.
Empower your FlowHunt AI agents with direct access to analytics, feature flag control, and error insights via PostHog MCP Server.
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