"TypeScript" matching MCP servers:

A stateless MCP server for incident lab operations, exposing MCP and health endpoints, with conformance testing.

TypeScript MCP server that enables AI agents to manage LangSmith traces, prompts, datasets, experiments, and billing through natural language.

A production-ready TypeScript template for building MCP servers with dual transport support (stdio/HTTP), OAuth 2.1 foundations, SQLite caching, observability, and security features including PII sanitization and rate limiting.

A TypeScript-based MCP server that enables users to interact with Prometheus metrics using PromQL queries and discovery tools. It allows LLMs to retrieve time-series data, metadata, alerts, and system status directly from a Prometheus instance.

An MCP server implementation for accessing Google Analytics 4 (GA4) data, built using the Model Context Protocol TypeScript SDK.

a typescript mcp to a langfuse MCP that enables you to see and connect agents to lanfuse data

Read-only local MCP server for inspecting AgentInspect TypeScript AI-agent traces. Lists runs, exposes bounded causal-failure and TraceFacts evidence, evaluates TraceContract checks, compares runs, and creates share-checked evidence without mutating traces or invoking agent tools.

Monitors development server logs in real-time and provides Claude with immediate error notifications via Server-Sent Events. Intelligently parses TypeScript, Svelte, and Vite errors with severity classification and file correlation.

A TypeScript MCP server for querying Shopee logs via the log platform's Mgmt API and Querymaster WebSocket flow, with config-driven service resolution and session reuse.

A local-first MCP server that gives AI coding agents runtime visibility and AI-managed debug logging. It replaces blind print() debugging by turning runtime execution into causal chains, allowing agents to instantly locate bugs by finding missing .success events in Python and TypeScript code. Single binary with MCP, CLI, and HTTP interfaces.

A TypeScript implementation of a Model Context Protocol server that connects to Sentry error tracking service, allowing AI models to query and analyze error reports and events.