"Using a search engine to find evidence to answer a question" matching MCP servers:

An evidence-first Prometheus MCP server that lets AI agents query production telemetry with detailed receipts including exact PromQL, timing, series count, and explicit warnings for empty, high-cardinality, or unreliable data.

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.

Prediction stability engine for AI agents. Evaluate model stability, detect ghosts, probe any LLM for instability, monitor fleet drift. 20 tools + 1 resource. Works with Claude, Cursor, VS Code.

Enables agents to check whether an execution trace contains the evidence needed for post-hoc causal reconstruction, retrieve individual requirement details, and list evidence requirements per failure class over MCP stdio. It works on files, directories, or inline JSON locally and never transmits or persists data.

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

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.

Enables ingestion and full-text search of Windows application logs via MCP tools. Supports dual-backend indexing with Elasticsearch and SQLite for fast retrieval.

MCP server for read-only investigation of Aliyun SLS logs fixed to cn-beijing/taient-rpa/node-rpa. Exposes search_logs, get_context_logs, and check_connection tools with a guided investigation skill.

Behavioral trust scoring for MCP servers and AI agents. Live registry tracking 4,500+ servers with trust scores (0-100) based on interaction history, success rates, and latency

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.

An MCP server that exposes a dbt project's run state as tools, enabling AI assistants to answer questions like 'is the warehouse healthy?' or 'what broke and why?' via plain English, using read-only access to dbt artifacts and warehouse data.

Enables an LLM agent to investigate a Kong Gateway through fourteen read-only, schema-validated tools and a deterministic diagnostic engine, so it can trace routes, services, plugins and upstream health and explain faults such as why authentication is failing on a path. Every fact comes from the gateway itself, and the model only selects tools and writes the evidence-backed explanation.

Postgres performance MCP server that analyzes hotspots, explains query plans, and detects dead-weight indexes. It aims to produce evidence-backed recommendations through a verification loop.

Enables agents to query GPU availability across SSH hosts, find free GPUs, list hosts, and inspect fleet status using only nvidia-smi on the remote side.

An MCP server that enables AI assistants to interact with Tenzir, a data pipeline engine for security operations, including executing pipeline queries, managing OCSF schemas, and generating parsers.

Enables querying OpenObserve logs—listing streams, inspecting schemas, and running SearchSQL time-windowed searches—so you can answer what actually happened in production. Optionally correlates those logs against a database through a verified read-only connection via DbSchema and DbQuery tools.

Diagnoses Postgres job queues (pg-boss, graphile-worker) to identify retry storms, stuck jobs, missed schedules, and other issues, providing evidence-based recovery steps.

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.