"High-Quality PDF Extraction to Text with Tokenization and Accurate Processing of Complex Layouts" matching MCP servers:

A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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

Enables AI clients to automatically investigate dbt test failures, trace root cause through BigQuery lineage, and generate plain-English incident reports.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Enables an AI assistant to diagnose a broken application on a local Kubernetes cluster by inspecting pods, events, and logs, with server-side guardrails, least-privilege RBAC, and an audit log. It can also restart deployments in allowed namespaces only after a dry-run preview and host approval.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Enables natural language analysis of network packet captures, including protocol detection, flow analysis, and security threat identification, integrated with AI assistants.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

Offline MCP server with runbooks for high-volume logs, metrics, traces, and event streams. Search and diagnose symptoms without external dependencies.

Enables agents to analyze large logs by clustering messages with Drain3 and returning a representative set of snippets from provided text, files, URLs, or compressed archives.

Provides a suite of 33 tools for interacting with Tencent Cloud Log Service (CLS), enabling log analysis, PromQL metrics queries, and resource management. It allows AI assistants to perform CQL/SQL retrieval, manage alarm strategies, and handle data processing tasks with tiered permission controls.

Enables agents to report and query performance metrics to build a community-driven quality database for MCP tools. This server helps agents discover and select the most reliable tools based on success rates and user-reported quality scores.

MCP server that reads Spark profiler files to give accurate Minecraft server tuning advice, parsing binary protobuf directly and diagnosing TPS, MSPT, GC, heap, and call-tree issues.

Bridges AI coding assistants with the OpenTelemetry ecosystem, providing real-time access to repositories, documentation, examples, semantic conventions, and instrumentation scoring for high-quality observability.

A Model Context Protocol (MCP) server that exposes lnav log file analysis capabilities to AI assistants, specifically optimized for Kvaser Plain Text Log Frame CAN bus log processing.

Enables natural-language querying and investigation of homelab logs from syslog, Docker, OTLP, and AI transcripts, with SQLite full-text search, timeline correlation, incident clustering, and fleet topology insights.

Exposes knowledge retrieval to AI tools over MCP with dense, sparse, and hybrid search, RRF fusion, configurable reranking, and modular ingestion of PDF/Markdown documents including image captioning. It also provides query tracing and Ragas-based evaluation so pipelines can be swapped, debugged, and tested independently.