"A way to find people on LinkedIn using their names" matching MCP servers:

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

A secure MCP proxy server with JWT authentication, SQL guardrails, rate limiting, and Kafka audit logging, enabling enterprise-grade access control for MCP clients like Cursor and Claude Desktop.

Unofficial MCP server for Vexo analytics. Enables querying event names, counts, timelines, sessions, and recent events from Vexo Export API through natural language.

Ariadne's thread — a way out of the microservice maze. Local cross-service semantic chain hinter for microservices (GraphQL/HTTP/Kafka/frontend)

Shows what is consuming your agent context window before a session starts: always-loaded skill descriptions ranked by token cost, skills installed more than once under different names, CLAUDE.md/AGENTS.md sizes including what their @import lines pull in, and MCP servers configured across clients. Read-only: no child processes, no network.

Provides a standardized way for MCP clients to interact with Apache Airflow's REST API, supporting operations like DAG management and monitoring Airflow system health.

A Model Context Protocol server that connects to AppSignal, allowing users to fetch, list, and analyze incident information from their AppSignal monitoring.

Connects MCP clients to Gemini Cloud Assist APIs, enabling users to understand, manage, and troubleshoot their Google Cloud environment using natural language.

Metered log ingestion server for autonomous agents, allowing NDJSON log posting with USDC payment per line on Base L2. Agents can freely tail and search their own logs with configurable retention tiers.

MCP server that analyzes AI agent session logs to find token waste and optimization opportunities.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

A Model Context Protocol server that connects to Veeam Backup for Microsoft 365 to review backup configuration, find protection gaps, and optionally run jobs and restores with opt-in safety controls.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Exposes live industrial IoT telemetry to any MCP client, streaming simulated sensor data from a fleet of machines and detecting anomalies, with the ability to inject faults on demand.