developer-tools

Agent Never Give Up

askman-dev

by askman-dev

Agent Never Give Up: structured thinking tools that help coding agents recover from stuck states quickly and reliably.

Structured thinking tools to help coding agents recover from stuck states

github stars

5

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Autonomous recovery without human handoffMetacognitive protocols for self-debugging

best for

  • / AI agents stuck in debugging loops
  • / Coding assistants losing track of main objectives
  • / Agents with unclear or expanding task scope
  • / Automated development workflows hitting analysis paralysis

capabilities

  • / 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

what it does

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

about

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

MIT

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.

readme

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

FAQ

What is the Agent Never Give Up MCP server?
Agent Never Give Up is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Agent Never Give Up?
This profile displays 36 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

List & Promote Your MCP Server

Share your MCP server with the developer community

GET_STARTED →
MCP server reviews

Ratings

4.536 reviews
  • Shikha Mishra· Dec 20, 2024

    I recommend Agent Never Give Up for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Amina Tandon· Dec 8, 2024

    We evaluated Agent Never Give Up against two servers with overlapping tools; this profile had the clearer scope statement.

  • Amina Okafor· Nov 27, 2024

    Agent Never Give Up is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Yash Thakker· Nov 11, 2024

    Strong directory entry: Agent Never Give Up surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Layla Wang· Oct 18, 2024

    Agent Never Give Up is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Dhruvi Jain· Oct 2, 2024

    Agent Never Give Up has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Hiroshi Singh· Sep 25, 2024

    Agent Never Give Up has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Layla Liu· Sep 25, 2024

    Agent Never Give Up is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Nia Ghosh· Sep 13, 2024

    Strong directory entry: Agent Never Give Up surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Oshnikdeep· Sep 9, 2024

    According to our notes, Agent Never Give Up benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

showing 1-10 of 36

1 / 4