Schema | ai-backend-performance-mcp

ai-backend-performance-mcp

Describes the environment variables required to run the server.

Name	Required	Description	Default
No arguments

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": true }

Functions exposed to the LLM to take actions

Name	Description
analyze_projectB	Analyze a Node.js backend project for performance issues across database, async, pooling, and dependencies.
analyze_database_queriesA	Detect MongoDB/PostgreSQL query anti-patterns such as N+1 queries, unbounded finds, and sequential query calls.
analyze_indexesB	Analyze MongoDB query patterns against createIndex definitions to surface potential missing indexes.
analyze_async_patternsB	Detect async performance issues including await in loops, sequential awaits, and blocking operations.
analyze_connection_poolingB	Detect database client or pool creation inside request handlers, loops, or other hot paths.
analyze_dependenciesA	Analyze package.json and lockfile for dependency hygiene issues including unused and misclassified packages.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/robinafaruqia/ai-backend-performance-mcp'

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