"Categorizing messages such as emails or system logs" matching MCP servers:

A production-grade MCP server with 6 sandboxed tools and an agent orchestration engine for autonomous task completion, featuring an evaluation suite with CI/CD quality gates.

A LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents.

Enables AI coding tools to validate local projects and publish or update applications to Bedengan App Hub via API, with automated checks and live deployment without manual approval.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

Detects breaking changes in a TypeScript library's public API and recommends the semver bump, comparing two npm releases, git refs or a working tree. Each finding is graded proven or review-only.

A Model Context Protocol server for Bitbucket Cloud that lets agents read pull request diffs, comments, and pipeline logs, as well as write PR comments and edit PR details.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

Read-only MCP server for Woodpecker CI that allows AI agents to check pipeline status and retrieve step logs across multiple self-hosted instances.

MCP server that lets Claude diagnose failed GitHub Actions runs by fetching and parsing CI logs into structured failure signals, enabling natural-language questions like 'Why did the last run fail?'.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp

CI health reports for GitHub Actions: flaky tests named from logs, wasted compute priced in dollars, zombie crons, PR feedback time, plus 21 lint rules with safe auto-fixes. Read-only MCP tools wrap the same Go binary.

Enables AI coding agents to see their Odoo.sh projects by listing projects, branches and builds, waiting for a build to finish, reading build and server logs, and optionally rebuilding branches or updating the firewall. It runs read-only by default with bounded, time-limited tool calls, keeping the user's Odoo.sh session out of the agent's reach.

MCP server for GitHub Actions CI failure triage. It wraps the gh CLI to fetch PR checks, failed jobs, and tail/grep failed job logs with ANSI/timestamp stripping and root-cause extraction.

Enables deployment and management of applications on the Citizen platform from git repositories or local files. It allows AI assistants to monitor deployment logs, handle authentication, and automatically fix build errors using intelligent error analysis.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

An MCP server that enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.

Lets any MCP-capable client connect to the public Codemagic REST API to list apps and teams, inspect build history, and optionally trigger or cancel builds and manage team settings. Runs locally over stdio with the user's own API token and configurable read-only, build, or administrative permission modes.

Checks whether software dependencies (npm packages, GitHub Actions, MCP servers, Docker images) are alive, dormant, abandoned, archived, or deleted using dated observations from lastseen.dev.

MCP server for JetBrains Space merge requests and Patronus CI dry runs, enabling creation, viewing, and management of merge requests as well as starting and monitoring CI dry runs.

Enables interaction with Rundeck instances to list jobs, execute jobs with options, and retrieve execution status and logs through natural language commands.

Enables analyzing Salesforce deployment logs, validating metadata manifests, assessing permission risks, and generating remediation plans through deterministic, local-only rules.

Enables inspection and management of Apache Airflow DAGs, runs, and logs across multiple instances. It provides tools for monitoring workflows and performing gated write operations like triggering DAGs or clearing task instances.

Enables AI coding agents to check Travis CI build status, identify failing jobs, and read job logs, with read-only access enforced via GET-only requests and a limited tool set.

Post-quantum readiness for AI coding agents: scans code for quantum-vulnerable cryptography (RSA/ECDH/ECDSA/DH) and returns NIST ML-KEM/ML-DSA/SLH-DSA (and hybrid) migration guidance, with fix verification and dependency checks. Content-based, advisory tools only; runs local (npx @quantakrypto/mcp) or as a hosted OAuth endpoint.

Enables AI assistants to query and manage Azure DevOps projects, boards, work items, repos, pull requests, and pipelines while enforcing governance boundaries such as access modes, project scoping, protected projects, delete gating, and typed confirmations.

Enables agents and CI pipelines to audit MCP servers and agent tool-chains by statically scanning repositories, local checkouts, tools/list exports, or live endpoints for risks such as destructive actions without confirmation, mismatched safety annotations, injection surfaces, credential or PII exposure, and unguarded command, path, or URL sinks. All checks are read-only and never execute the scanned code or call tools/call.

Enables AI assistants to deploy and manage SnapDeploy containers and resources—including builds, logs, environment variables, databases, and custom domains—directly through natural language.

Enables AI assistants to deploy, manage, and rollback websites via the Krexel API, supporting site uploads, deploys, logs, rollbacks, environment variables, and status checks.

Triage failing DeviceCloud runs by pulling failure evidence (screenshots, logs, analytics) into your editor so an AI assistant can diagnose and fix issues without opening the dashboard.