Prometheus is an open-source systems monitoring and alerting toolkit. It collects and stores metrics as time series data, with flexible queries and real-time alerting.
Fronts the Prometheus MCP server (shipped as a mock in the repo and available as a real server), routing requests to PromQL queries, metric names/metadata, and scrape target tools.
Enables agents to connect through a single gateway that has a decision model pick which MCP tools and playbooks are relevant to each request, so the LLM only sees the few schemas it needs, and to then invoke those tools on the underlying servers. This cuts tool-selection cost and prompt size dramatically when many MCP servers are connected.
2
4
MIT
Why this server?
Enables metrics management and querying through support for Prometheus remote_write/read and PromQL.
ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.
10
1,226
Apache 2.0
Why this server?
Exposes metrics in Prometheus format for monitoring the MCP server's performance and usage.
Self-hosted semantic code search for AI coding agents. Indexes many repositories at once with tree-sitter AST chunking, local llama.cpp embeddings and Qdrant, so Claude Code, Cursor, Codex and any MCP client can find code by meaning, trace usages and callers, and read the git history behind each chunk. No API keys, and your code never leaves your machine.
2
18
34
MIT
Why this server?
Provides a tool to retrieve BlazingCDN metrics in Prometheus format, enabling monitoring and alerting with Prometheus.
Official MCP server for BlazingCDN - AI agents (Claude, Cursor, Windsurf) manage CDN resources, purge cache, query metrics, domains, Cloud Storage and Video CDN
29
27 npm
2
MIT
Why this server?
Allows querying Prometheus metrics via prometheusQuery* table functions.
An MCP server for chDB, the in-process SQL OLAP engine powered by ClickHouse. Lets agents query Parquet, CSV, JSON, and pandas DataFrames with one tool — no separate server, no Docker.
7
Apache 2.0
Why this server?
Provides architecture-aware visual styling for Prometheus monitoring components within Excalidraw diagrams.
An MCP server that generates beautiful Excalidraw architecture diagrams with perfect auto-layout, stateful editing, and architecture-aware component styling.
2
26
397 PyPI
160
MIT
Why this server?
Reads and remote-writes per-pattern volume and cost series to a Prometheus backend using PROMETHEUS_REMOTE_WRITE_URL / PROMETHEUS_URL, enabling per-pattern metric backfill and queries.
Ranks log patterns by volume and cost on Splunk, Datadog, Elasticsearch, CloudWatch and ClickHouse, and plans compact, tier down or offload for the excess over each cap. Runs locally over stdio; no log data reaches log10x. Read-only against a public demo dataset without an API key.
56
4,345 npm
1
MIT
Why this server?
Allows monitoring Prometheus endpoints and metrics as a check type, and exposes /metrics.
Uptime monitoring from your AI agent: create and diagnose checks (40 types: HTTP, TCP, DNS, SSL, ICMP, databases, message queues and more), read results and incidents, and manage status pages and maintenance windows. Built into the self-hostable SolidPing server, served over streamable HTTP at /api/v1/mcp.
23
27
AGPL 3.0
Why this server?
Integrates with Prometheus for monitoring fleet conservation balance, convergence metrics, and agent status metrics.
Enables Claude Code to query and control the SuperInstance fleet, including fleet status, conservation law checks, semantic search, and agent registry.
