Agent Never Give Up

Agent Never Give Up

Official
askman-dev

Provides structured debugging protocols to help AI coding agents break out of stuck states and resume productive work without human intervention.

Structured thinking tools to help coding agents recover from stuck states

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What it does

  • Break circular reasoning loops with structured thinking protocols
  • Generate fresh debugging strategies when bug fixes repeatedly fail
  • Identify missing requirements blocking progress
  • Refocus work when scope creep occurs during tasks
  • Realign current actions with original objectives
  • Reset complex logic into manageable steps

Best for

AI agents stuck in debugging loopsCoding assistants losing track of main objectivesAgents with unclear or expanding task scopeAutomated development workflows hitting analysis paralysis
Autonomous recovery without human handoffMetacognitive protocols for self-debugging

About Agent Never Give Up

Agent Never Give Up is an official MCP server published by askman-dev that provides AI assistants with tools and capabilities via the Model Context Protocol. Agent Never Give Up: structured thinking tools that help coding agents recover from stuck states quickly and reliably. It is categorized under developer tools. This server exposes 9 tools that AI clients can invoke during conversations and coding sessions.

How to install

You can install Agent Never Give Up in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.

License

Agent Never Give Up is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

Tools (9)

list_scenarios

List all available stuck-agent scenarios with their tier (core/extended). Core scenarios are also directly available as individual tools.

bug-fix-always-failed

Use this when your bug fix attempts keep failing, and you need to break out of the loop with a fresh debugging strategy.

logic-is-too-complex

Use this when your reasoning is getting long, tangled, or circular, and you need a simple, structured way to reset and move forward.

long-goal-partially-done

Use this when working on a multi-step task and you have only completed part of it, risking that remaining steps are forgotten.

lost-main-objective

Use this when you remember the original goal but your current actions feel disconnected from it, and you need to realign your work with the main objective.

Agent Never Give Up MCP

This is a MCP server that acts as a "escape guide" for AI coding agents.

It provides structured thinking protocols to help agents unstuck themselves without human help.

The diagram below illustrates when an agent should call this server and what it receives in return:

graph TD
    %% 1. The Normal Loop
    UserLoop["<b>User Query & Agent Loop</b><br/>(Claude Code / Windsurf / Cursor)<br/>Agent executing tasks..."]

    %% 2. The Problem (Triggers)
    subgraph Triggers ["Agent Gets Stuck (Trigger State)"]
        direction TB
        S1["Circular Reasoning"]
        S2["Bug Fix Fails"]
        S3["Missing Info"]
        S4["Analysis Paralysis"]
        S5["Unclear 'Done' State"]
    end

    %% Flow: Loop -> Stuck
    UserLoop -.->|"⚠️ Detects Issue<br/>(Inner Loop Stall)"| Triggers

    %% 3. The Solution (MCP Call)
    subgraph MCP ["Agent Never Give Up MCP"]
        direction TB
        T1(logic-is-too-complex)
        T2(bug-fix-always-failed)
        T3(missing-requirements)
        T4(analysis-too-long)
        T5(unclear-acceptance-criteria)
    end

    %% Mapping Triggers to Tools
    S1 -->|Call| T1
    S2 -->|Call| T2
    S3 -->|Call| T3
    S4 -->|Call| T4
    S5 -->|Call| T5

    %% 4. The Response
    MCP -->|Returns| R1["<b>Metacognitive Protocol</b><br/>Structured markdown to:<br/>1. Re-anchor goal<br/>2. Summarize failures<br/>3. Propose NEW strategy"]

    %% 5. The Outcome
    R1 --> Result["<b>Autonomous Recovery</b><br/>Agent unblocks itself &<br/>resumes execution<br/>(No Human Hand-off)"]

    %% Cycle back to loop
    Result -.->|"Resumes Loop"| UserLoop

    %% Styling
    classDef loop fill:#e1f5fe,stroke:#01579b,stroke-width:2px;
    classDef trigger fill:#ffebee,stroke:#b71c1c,stroke-width:2px;
    classDef tool fill:#fff3e0,stroke:#e65100,stroke-width:2px;
    classDef response fill:#e8f5e9,stroke:#1b5e20,stroke-width:2px;
    
    class UserLoop loop;
    class S1,S2,S3,S4,S5 trigger;
    class T1,T2,T3,T4,T5 tool;
    class R1,Result response;

Features

  • Remote MCP server at /mcp endpoint (Streamable HTTP specification compliant)
  • Two-tier scenario organization:
    • Core scenarios (auto-registered as direct MCP tools):
      • logic-is-too-complex – for circular reasoning or over-complicated logic
      • bug-fix-always-failed – for repeated failed bug fix attempts
      • missing-requirements – for unclear or missing requirements
      • lost-main-objective – for when current actions feel disconnected from the original goal
      • scope-creep-during-task – for when changes expand beyond the original task scope
      • long-goal-partially-done – for multi-step tasks where remaining work is forgotten
      • strategy-not-working – for when the same approach fails repeatedly
    • Extended scenarios (discovered via list_scenarios, accessed via get_prompt):
      • analysis-too-long – for excessive analysis time
      • unclear-acceptance-criteria – for undefined acceptance criteria
      • wrong-level-of-detail – for working at wrong abstraction level
      • constraints-cant-all-be-met – for conflicting requirements or constraints
      • blocked-by-environment-limits – for environmental blockers vs logic problems
  • Discovery tools:
    • list_scenarios – list all scenarios with their tier (core/extended)
    • get_prompt – access any scenario (core or extended)
  • Dual mode support: Each tool supports static and sampling modes
  • Community-contributed prompts via markdown files
  • Public and auth-less (v0)
  • Cloudflare Workers deployment

Configuration

Since agent-never-give-up is a cloud-hosted MCP server, no local installation is required. Simply add the server configuration to your preferred AI tool.

Install in Cursor

  1. Open Cursor Settings > MCP.
  2. Click + Add new global MCP server.
  3. Use the following configuration (or edit your ~/.cursor/mcp.json file directly):
{
  "mcpServers": {
    "agent-never-give-up": {
      "type": "http",
      "url": "https://agent-never-give-up-mcp.askman.dev/mcp",
      "note": "A 'Swiss Army knife' toolset to help agents recover from getting stuck"
    }
  }
}

Install in Claude Desktop

To configure the server for Claude Desktop, edit the configuration file located at:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Add the following entry to the mcpServers object:

{
  "mcpServers": {
    "agent-never-give-up": {
      "type": "http",
      "url": "https://agent-never-give-up-mcp.askman.dev/mcp"
    }
  }
}

Install in Cline

  1. Open Cline and click the MCP Servers icon (☰).
  2. Select the Remote Servers tab (if available) or click Configure MCP Servers.
  3. Edit the cline_mcp_settings.json file to include:
{
  "mcpServers": {
    "agent-never-give-up": {
      "type": "http",
      "url": "https://agent-never-give-up-mcp.askman.dev/mcp",
      "note": "A comprehensive suite of tools designed to keep agents persistent and unstuck"
    }
  }
}

Install in Windsurf

  1. Open Windsurf.
  2. Go to File > Settings > Configure MCP Servers (or edit ~/.codeium/windsurf/mcp_config.json).
  3. Add the server configuration:
{
  "mcpServers": {
    "agent-never-give-up": {
      "type": "http",
      "url": "https://agent-never-give-up-mcp.askman.dev/mcp"
    }
  }
}

Development

To contribute to this project or run a local instance:

# Install dependencies
npm install

The local server will be available at http://localhost:8787/mcp.

Contributing Prompts

Prompts are organized in two tiers within the prompts/ directory:

prompts/
├── core/                           # Core scenarios (auto-registered as tools)
│   ├── logic-is-too-complex/
│   │   └── tool.md
│   ├── bug-fix-always-failed/
│   │   └── tool.md
│   └── missing-requirements/
│       └── tool.md
└── extended/                       # Extended scenarios (via list_scenarios + get_prompt)
    ├── analysis-too-long/
    │   └── tool.md
    └── unclear-acceptance-criteria/
        └── tool.md

Prompt File Format

Each tool.md file follows a simple markdown format with YAML frontmatter and a single protocol body:

---
name: scenario_name
title: "Scenario Title"
description: "When / why the agent should call this tool, from the agent's perspective"
---

When you notice [the trigger condition], follow this exact protocol step by step.

## 1. First step title

1. Action item one.
2. Action item two.
3. Action item three.

Keep it concrete.

## 2. Second step title

...

## 3. Third step title

...

Key principles:

  • The description explains when to use the tool (the trigger condition)
  • The body is a single protocol with numbered sections
  • Each section has 2–6 concrete steps
  • Focus on how to think, not domain-specific details
  • No system prompt / user prompt template sections—just one actionable protocol

See prompts/AGENTS.md for detailed guidance on writing effective prompts.

Adding a New Scenario

Scenarios are auto-discovered from the prompts/ tree and the generated files in src/prompts/generated-scenarios.ts and src/types/generated-scenarios.ts. You do not need to manually edit TypeScript files—just add the prompt and regenerate.

Core scenarios (auto-registered as tools):

  1. Create a new directory: prompts/core/{scenario_name}/ (must match /^[a-z0-9]+(-[a-z0-9]+)*$/).
  2. Add a tool.md file following the format above.
  3. Run npm run generate:scenarios to regenerate types and discovery data.

Extended scenarios (accessible via get_prompt):

  1. Create a new directory: prompts/extended/{scenario_name}/ (same naming rules as above).
  2. Add a tool.md file following the format above.
  3. Run npm run generate:scenarios to regenerate types and discovery data.

Deploy

# Deploy to Cloudflare Workers
npm run deploy

After deployment, your MCP endpoint will be: https://agent-never-give-up-mcp.<account>.workers.dev/mcp

License

MIT

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