"Capture The Flag (CTF) cybersecurity competitions and challenges" matching MCP servers:

Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded in your code and stored as git-tracked JSON reviewed in PRs, with citations validated on write and stale memory withheld from recall. Works with any MCP client.

Enables coding agents to connect to Debug Adapter Protocol debuggers over MCP, allowing them to launch or attach to native targets, control execution, set breakpoints and watchpoints, inspect stacks, variables, memory, and exceptions, and capture agent-friendly debugger snapshots.

Enables MCP-capable clients to query the tool registry, check install status, get tool recommendations for CTF or bug-bounty work, and run installed security tools through a governed execution path.

Enables MCP clients to run a two-agent coding workflow where one AI plans and implements while another reviews, challenges and cross-examines, iterating until consensus and then verifying the result with a real test command. It also exposes persistent session tools to check status, read the transcript, inject notes mid-run, and cancel work.

Enables pi coding agent users to run Pega Infinity authoring tools as native pi tools, with read-only access by default and write tools behind an explicit opt-in flag.

Enables MCP clients to read a project's component tree and design tokens, edit React/TSX canvas frames, set props, apply auto layout and variants, add shader backgrounds, and capture screenshots, so agents can make design changes that are written back as reviewable code diffs and pull requests.

dev-brain-mcp

An MCP server that allows Pebble Index to capture notes, enqueue tasks, create follow-ups, and launch visible Codex threads on a Windows PC. It uses a remote server with token-based access and a local runner that executes only explicit execution requests.

Provides persistent memory and task management for coding agents via MCP tools, enabling mid-session recall and capture of durable knowledge.

Enables MCP-compatible clients like Codex to delegate tasks to the Antigravity CLI, using ConPTY on Windows to reliably capture responses.

An MCP server that provides persistent project context, workflow management, and knowledge capture for AI coding agents. It enables agents to maintain structured memory across sessions by tracking project profiles, conventions, skills, and technical debt.

A code understanding and generation system designed for Galacean Engine that helps LLMs comprehend the engine architecture and generate high-quality engine code based on user intent.

Plori runs AI agents in Workspaces. A Workspace is a project folder in the cloud. Several agents can work in it at the same time, each on its own copy of the files, and Plori merges their work back into the folder. Every version of the files is kept.

MCP server that delegates bounded subtasks to NVIDIA NIM sub-agents, enabling context offload and parallel fan-out for coding assistants like Claude Code and Cursor.

An MCP server giving coding agents context-window-aware code search and safe, atomic multi-file edits — built to cut token usage on large codebases without sacrificing correctness.

Enables structured, step-by-step problem-solving through dynamic thinking processes that can be revised, branched, and adjusted as understanding deepens. Supports breaking down complex problems into manageable steps with the ability to revise previous thoughts and explore alternative reasoning paths.

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.

Provide a human vision statement. The AI autonomously researches, audits your codebase, generates specs and plans, implements, and validates — with bi-directional verification at every junction to ensure nothing is missed or invented.

Enables AI coding agents to retrieve relevant execution context before a task, compare candidate paths, log outcomes, and search past experiences stored locally in SQLite. It lets agents reuse what worked on similar tasks and get live alerts when a run stagnates or repeats failures.

Enables delegating coding tasks to isolated Claude Code subprocesses billed against a GLM Coding Plan, with tools to delegate, await, continue, list, cancel, and inspect runs.

Provides brutally honest code reviews, explanations, and refactoring suggestions via CLI and MCP tools.

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

Provides TypeScript and JavaScript code refactoring operations using ts-morph, allowing AST-based symbol renaming, file/folder renaming, reference searching, and path alias removal when integrated with editor extensions like Cursor.

An MCP server that allows coding agents to search the Swift Package Index and retrieve GitHub READMEs without requiring an API key. It features comprehensive search filters for stars, platforms, and licenses, providing token-efficient responses optimized for LLM comprehension.

Scoped, low-latency persistent memory layer for AI agents, Cursor, and Claude Code over Model Context Protocol with sub-50ms hybrid search.

Exposes the four Ejentum cognitive harnesses (reasoning, code, anti-deception, memory) as MCP tools any agentic client can call. Drop-in scaffolding that catches LLM failure modes like sycophancy, hallucination, and reasoning shortcuts.

Provides a persistent memory and governance layer that allows AI coding agents to query documented architecture rules and validate code against team standards. It enables agents to verify compliance across categories like security and testing before suggesting changes to ensure consistency across development sessions.

This server lets MCP clients delegate coding tasks to a locally installed Qwen Code CLI, enabling second opinions, parallel work, and clean separation from the main context.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

Enables Claude Code to use GLM (Zhipu) as a cheap, full-capability subagent for file editing, code generation, and bash commands, with automatic routing between Opus and GLM based on task complexity.