MCP Servers for Observability

Cryptographic accountability for AI agents. Ed25519-signed receipts for every MCP tool call. Constraints, chains, AI judgment, invoicing, and local dashboard included.

Data freshness verification for AI agents. Probes endpoints for HTTP cache staleness, latency percentiles, content fingerprinting, TLS certificate health, DNS timing, and redirect chains. Returns deterministic FRESH/STALE/UNKNOWN JSON verdicts with policy evaluation and NIST AI RMF mapping.

Enables interaction with Foreman instances to manage systems through the Model Context Protocol. It provides access to Foreman resources and tools, such as security update reports, directly within AI-powered environments like VSCode and Claude Desktop.

Enables language models to access LangSmith observability platform features including fetching conversation history, managing prompts, retrieving traces and runs, working with datasets and examples, and analyzing experiments.

Enables AI assistants to interact with Rollbar error tracking and monitoring service, allowing them to diagnose issues, view item details, list deployments, retrieve session replays, and update item properties through natural language commands.

Query Langfuse traces, schema and datasets, scores and metrics, debug exceptions, analyze sessions, and manage prompts. Full observability toolkit for LLM applications.

Lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things on your Cloudflare account.

MCP server that reads Duplicacy backup metrics from a Prometheus exporter and exposes them to LLMs for monitoring backup status, progress, and health.

A Model Context Protocol server that enables LLMs to retrieve and analyze OpenTelemetry traces and metrics from Logfire, supporting exception tracking and custom SQL queries against telemetry data.