"Information or connection related to Zed, Roo Code, and Goose" matching MCP servers:

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.

MCP server that provides read-only analysis of Claude Code session transcripts, enabling queries about project activity, session details, and tool usage.

A Model Context Protocol server for Zoho Site24x7 that uses a JavaScript sandbox to execute API calls, enabling management of monitors, accounts, and MSP/BU tenancy through natural language.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Maintenance, recovery, and observability for Claude Code. CLI + MCP server + dashboard.

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.

Echo tool MCP server that extracts and logs W3C Trace Context from requests to verify propagation from Claude Code.

Surface Claude Code token usage, estimated cost, and plan-limit status in any MCP client. Enables agents to query usage data from local logs and Anthropic API.

Claude Code token usage and cost visibility for MCP-capable agents.

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.

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.

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.

Enables MCP clients to query and triage security findings published to BigQuery and correlate them with execution, sandbox, and diagnostic traces in Cloud Logging. Exposes tools, resources, and prompts for filtering issues by severity, status, repository, or CWE, retrieving patch diffs and verification results, and diagnosing why a remediation or verification run failed.

Enables Claude to discover and understand infrastructure-as-code drift by listing projects with drift, analyzing Terraform plan outputs, and providing remediation information.

A specialized diagnostic framework that enables AI models to self-diagnose and fix MCP-related issues by analyzing logs, validating configurations, testing connections, and implementing solutions.

Enables AI assistants to inspect uptime monitoring, incidents, status pages, alerts, dependencies, and reports. It also supports related changes such as opening incidents, posting updates, scheduling maintenance, adding monitors, and configuring alerts and reports.

Enables AI agents to inspect a running VS Code webview or extension host in real time, exposing DOM, console, state-store, performance, and message-traffic data over a stdio connection. Tool activation is config-driven, so MobX, Redux, Zustand, or Apollo store tools and backend-side tools appear only when the corresponding adapters are wired up.

Enables AI assistants to interact with tshark and related command-line tools for live packet capture, PCAP analysis, filtering, stream following, and capture file merging.

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.

Enables on-call database diagnostics: it classifies load pressure, traces root causes with hypothesis-evidence-confidence, detects blocking and lock chains, scores health across a dimension tree, and renders deliverable incident reports. Works from symptom text alone with no database connection or history required (Tier0), escalating to snapshot-based and trend-based analysis as observations accumulate.

Enables interaction with Prometheus Alertmanager for querying alerts, managing silences, and investigating incidents. Supports direct API connection and Kubernetes auto-discovery.

Provides secure, multi-user access to Oracle Database for MCP clients, enabling SQL querying, execution, schema exploration, and performance analysis through various connection methods including TNS, JDBC, and TCPS.

Enables AI coding agents to access live console logs, errors, and network requests from web applications via a local WebSocket connection, without copying data to chat.

Enables read-only querying and analysis of Kibana logs through a logged-in sid Cookie, including keyword/time/index searches, traceId lookups, surrounding log context, and aggregations by service, level, or host. It also validates Kibana connection status and redacts sensitive fields such as cookies, tokens, and passwords.

Read-only MCP server that surfaces UniFi network data from a UCG-Fiber console to Claude, enabling monitoring of hosts, sites, devices, clients, ISP metrics, and device stats via read-only API tools.

Read-only MCP server providing Microsoft 365 service health status and known incident/outage information from Microsoft Graph. Enables quick answers to whether an issue is a widespread Microsoft outage or specific to a tenant.

Enables retrieval of error stack traces by transaction ID from OpenSearch logs, supporting configurable connection settings and Docker deployment.

Connects AI assistants to live VuNet observability data, allowing querying metrics, browsing data models, and checking connection status.

An MCP server that connects to Sentry.io or self-hosted Sentry instances to retrieve and analyze error reports, stack traces, and debugging information.