"A guide to finding people on LinkedIn by 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.

Enables assistants to securely work on a Chest via personal access token: reading tool logs, builds, and databases, editing rows and variables, and installing or linking tools, with every write requiring a dry run and human confirmation.

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

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.

Lets agents query their own usage ledger captured by the Agentic Ledger proxy: sessions with full call traces, costs, loop runs, and stuck-loop flags. Tools include list_sessions, get_session, search, list_runs, get_run_status, and explain.

Enables querying OpenTelemetry logs stored in OpenSearch across development and production environments. Provides tools for searching logs by various criteria including free-text Lucene queries, trace IDs, service names, error levels, and specific fields.

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.

Ships only the MCP server, not the recorder. Recording works by wrapping a process on the host — a local proxy, a PATH shim, a shadow git index. None of that survives a container boundary, so orca record inside here would watch an empty namespace. What does travel is the read side: the six MCP tools serve runs that already exist on disk, so a client mounts its .orca directory and r

Enables an MCP-capable agent to operate a heterogeneous cluster of Debian/Armbian Linux nodes over SSH from a single inventory, inspecting status and logs, managing packages, services, files, storage and NFS, and deploying new capabilities to nodes through installable modules. Built-in cluster tools fan out to nodes by explicit names, roles or tags with bounded concurrency, while modules can be installed on compatible nodes and run on demand or as systemd services.

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.

Enables an AI assistant to diagnose on-premise Windows pm2-managed Node/Nitro services by answering read-only questions about deployed builds, process liveness, logs, current configuration, and whether the running process started with the configuration currently on disk.

Enables AI assistants to list OpenObserve log streams, inspect their schemas, and run read-only SELECT queries with enforced safety caps.

Provides read-only, multi-vendor network device interaction, configuration auditing against vendor-guide rules, and safe diffing of proposed changes for AI agents to inspect and analyze network infrastructure without any commit or write capability.

Guardrail sidecar proxy between AI agents and their MCP/REST/CLI tools. Policy engine, human approval gates, time-limited grants, rate limiting, and OTEL tracing. One Go binary, one YAML config, fail-closed by default.