"A tool for reading PDF files" matching MCP servers:

A read-only MCP server that exposes local coding-agent session logs as three tools for introspection of recent work, debugging tool failures, and tracking token usage and estimated cost without parsing log files.

Local-first dashboard + MCP server that parses Claude Code and Codex JSONL files into a SQLite cost / token tracker. Per-MCP and per-tool breakdown, session drill-down, dedup by request_id; never talks to vendor APIs

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Enables observability and governance for local LLMs via Ollama, including auditing model usage, scanning prompts for secrets/PII, and enforcing allow/deny policies.

Provides structured access to Claude Code agent log files, allowing agents to query assistant lines and tool calls without reading raw JSONL data.

Enables LLMs to analyze Linux perf data files using 26 perf analysis commands, including report, script, annotate, and more, through typed tool parameters.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

A FastMCP-based tool for interacting with Splunk Enterprise/Cloud through natural language. This tool provides a set of capabilities for searching Splunk data, managing KV stores, and accessing Splunk resources

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 flight recorder for Claude Code that captures tool calls and observations into a SQLite database, then classifies them into a distilled timeline for incident troubleshooting.

MITM proxy MCP server that intercepts and verifies AI agent tool calls, detecting fabrication, tracking costs, verifying outcomes, and inferring user satisfaction.

A live post-mortem debugger MCP server for Home Assistant that lets AI agents list captured exceptions, walk traceback frames, read local variables, and optionally evaluate Python in the context of a captured frame for true post-mortem debugging.

A verifying MCP gateway that pins approved tool manifests and skill files to content addresses, blocking tampered descriptions before they reach model context.

An enterprise MCP server scaffold that provides secure, governed access to internal tools through RBAC, audit logging, rate limiting, and prompt-injection boundaries, with a FastAPI control plane and OpenTelemetry observability.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.

A MCP server for tracking AI usage metrics and structured logs across applications. Monitor model calls, analyze usage patterns, track costs, and debug AI interactions.

A safety layer and monitoring copilot for AI agents using Splunk MCP, recording tool calls, enforcing policies, and blocking risky actions.

SpineFrame is a audit-grade runtime that gives AI agents auditable provenance — every tool call, every piece of evidence, every decision is traced, policy-checked, and cryptographically signed. Signed evidence chains, compliance pipelines, and tool-call tracing that survives regulatory scrutiny.

Tripwire detection for autonomous AI agents. Plants honeypot files, MCP tripwire tools, and API decoy endpoints to log agent scope creep and unauthorized tool use with full forensic context.

A command-line tool for monitoring and analyzing New Relic application metrics using MCP.