"Official Atlassian MCP Server by Atlassian" matching MCP servers:

Enables AI assistants to interact with Bitbucket Cloud workspaces, repositories, branches, commits, and pull requests through MCP tools for listing, fetching, searching, commenting, reviewing diffs, and managing repository workflows such as cloning and PR operations.

Context compiler for AI coding agents that indexes TypeScript codebases to extract and serve only the relevant symbols and files for a task, reducing token usage and search overhead.

Adds symbol-aware semantic search to coding agents like Codex CLI and Claude Code, enabling precise codebase context via natural language queries.

Enables coding agents to retrieve structured, verified Jira/JSM issue briefs, pin root-cause code symbols, and report failing-to-passing test outcomes through Atlassian Rovo MCP.

Local MCP server for .NET developers: lets Claude read real NuGet packages at your pinned version, explore your C# code, and edit and build with approvals and secret hiding - configurable in Admin UI. Windows, SQLite,

An MCP server that performs code reviews by comparing local source code against design documents stored in Confluence. It integrates with Atlassian MCP servers to analyze documentation and provide suggestions for quality improvement based on design specifications.

Transforms local Git repositories into queryable, context-rich knowledge bases via AST-aware chunking and Git metadata, enabling AI assistants to search and understand codebases with semantic precision.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.

Helps ground AI agents in reality by fact-checking responses against official documentation and reading project files to prevent hallucinations during coding sessions.

Read, inspect and navigate codebase symbols by connecting to a Language Server

Enables checking Minecraft Bedrock content before it ships by validating JSON, commands, scripts, Python and whole packs against official schemas, a real tsc, and version-pinned game data, and by looking up whether identifiers, versions and fields actually exist. It reports what will silently fail to load — including errors schemas structurally cannot catch — without generating or writing anything itself.

Enables Codex to access C# diagnostics, navigation, and refactorings through the official Roslyn language server, including definitions, implementations, references, renames, fixes, and refactorings.

Generates customized, production-grade MCP servers for Rocket.Chat by selecting only the specific API endpoints needed for a project to minimize context bloat and token usage. It uses natural language processing to parse official OpenAPI specs and automatically create optimized TypeScript servers with built-in authentication and tests.

Connects a GeneXus knowledge base and curated official documentation to MCP-compatible AI assistants, enabling governed read/search, call-graph and impact analysis, versioned plans with rollback, draft generation, SDK probes, and official-knowledge queries through controlled tools.

Enables querying any GitHub, GitLab, or Bitbucket repository and getting AI-generated answers about the codebase, powered by Gemini.

Enables AI coding agents to efficiently navigate and understand large codebases by providing tools for entry point location, call chain analysis, and impact assessment, reducing context consumption and model costs.

Enables LLMs to apply Martin Fowler's 71+ refactoring patterns to codebases through a pluggable, language-agnostic architecture. Supports previewing and applying refactorings, analyzing code smells, and inspecting code structure with safe-by-default operations.

Enables LLMs to efficiently navigate and analyze large diff files by providing pattern-based chunk navigation, allowing direct access to relevant changes without loading entire diffs into context.

Official Codna MCP server with Mojo-powered risk simulation. Maps repos with zero LLM tokens. 5 stdio tools: triage, root-cause analysis and fix plans (optional PRs), SARIF reachability proof, on-device code memory and bug reporting. Introspection needs no credentials; execution requires a one-time free codna login. Source: cli/codna/mcp_server.py. Registry: io.github.thyn-ai/codna.

Enables AI coding assistants to debug and analyze JavaScript in web pages by managing scripts, breakpoints, network and WebSocket traffic, browser state, and local file inputs/outputs for continuous reverse-engineering workflows.

Indexes codebases cut at function and class boundaries into Oracle AI Database 26ai, letting AI coding tools search code by name or meaning, trace callers, callees and change impact, read per-module wiki pages, and recall facts from earlier sessions. All of it is served over the Model Context Protocol with embeddings computed in-database, so no source code leaves the machine and no API key is required.

Serves token-efficient code context for AI coding assistants by exposing Python signatures, call graphs, and budget-packed task context as MCP tools, enabling precise codebase queries without reading entire files.

Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.

Enables static security audit of Solidity smart contracts by analyzing source code or deployed bytecode for vulnerabilities, providing risk scores and detailed findings.

Static scanner for MCP/agent-gateway readiness anti-patterns, providing a 7-dimension R/Y/G score by scanning code and config for common failure modes.

A code review tool that generates detailed HTML review documents by comparing branches or commits, with author filtering and intelligent analysis.

Enables auditing the AI models and SDKs in a repository, drafting evaluation examples, ranking candidates by cost per passing answer, and generating cheapest-first routing configurations, all through read-only local tools that never make network calls. Also estimates monthly token spend and local weights/KV-cache memory so users can pick and size the cheapest model that passes their own tests.

Zero-dependency context baton and compression server for AI coding agents. Hands off structured session state (.vicem/BATON.md) across Claude Code, Codex, Cursor, Gemini CLI, and 15+ agents, skeletonizes source code by 80-90% with lossless on-demand MCP rehydration (vicem_rehydrate), slims test logs by 95%, and redacts secrets locally.

MCP server that exposes pre-extracted facts about code behavior, design decisions, and assumptions to AI agents, saving time and tokens by avoiding direct source file reading.

An MCP server for SonarQube that enables LLM agents to discover projects, analyze code quality metrics, check Quality Gate status, search issues with filters, and rank projects by worst-performing metrics. It provides read-only, safe access to SonarQube instances with structured outputs and error handling.

Knot is a semantic and structural codebase indexer designed for AI coding agents and developers navigating large projects. It combines vector search and graph traversal to find code by meaning, analyze impact via reverse dependencies, and explore file architectures.

AI-powered QA testing platform — catches JS errors, accessibility failures, visual regressions, API loops, security issues, and more via Chrome DevTools MCP

Provides instant GDScript syntax validation and diagnostics by bridging Godot's native Language Server Protocol to MCP clients. Enables real-time syntax checking in AI assistants without requiring custom plugins or context switching to the Godot editor.

AST-targeted code editing MCP server with 28 surgical tools for structural edits across 11 languages. Built on tree-sitter, replaces brittle search/replace with byte-correct edits keyed by symbol names.

Generates legal policies (privacy, terms, cookies, etc.) directly from AI coding tools by analyzing codebase context.

Enables coding agents to identify likely runtime failures in JavaScript and TypeScript by ranking risky files, tracing dependencies, analyzing logs, and obtaining independent model reviews with line-level reasons.

Translates a lockfile diff into a human-readable upgrade plan. For every dependency bump (npm or PyPI) returns semver class, breaking changes from GitHub release notes, CVEs fixed in the range, migration guide links, and a clear per-package recommendation. Bulk tool ranks up to 50 package changes in parallel by risk (security > caution > review > likely-safe > safe).

Enables LLM agents to explore JavaScript/TypeScript repositories through parsed syntax trees by returning compact file outlines, precise symbol definitions, and local dependency graphs. It keeps access read-only and sandboxed to chosen roots while using a bounded, flood-proof stdio transport.

Enables AI assistants to monitor GitHub repository health by calculating health scores, fetching repository metadata, analyzing Dependabot alerts, checking CI/CD status, and retrieving code scanning alerts.

MCP server that helps AI coding agents understand a repository by providing lightweight tree/map, code search, and token-budgeted context packing tools without dumping the entire monorepo into the prompt.