Nibble
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@NibbleCheckout is failing. Investigate and find root cause."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Nibble
Nibble is an AI-powered production incident investigation prototype built with the Model Context Protocol (MCP) and the OpenAI Agents SDK.
What it does
Nibble exposes production observability data through an MCP server, including:
Service health
Service logs
Recent deployments
Deployment details
An OpenAI agent can use these tools to autonomously investigate production incidents and identify likely root causes.
Related MCP server: MCP Observability Server
Example
Prompt:
Customers are reporting that checkout is failing. Investigate the incident and determine the likely root cause. Then indicate which deployment(s) caused it and who is responsible for the deployment(s).
Agent run output:
The agent can autonomously:
Check service health
Identify degraded services
Inspect relevant logs
Correlate failures with recent deployments
Inspect deployment changes
Determine a likely root cause
Architecture
OpenAI Agent
|
| MCP / stdio
v
Nibble MCP Server
|
+-- get service health
+-- get service logs
+-- get deployments
+-- get deployment details
|
v
Mock production dataRunning locally
Install dependencies:
npm installCreate a .env file:
OPENAI_API_KEY=your_api_keyRun:
npx tsx src/agents.tsTool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
No tool schema history has been recorded yet.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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