unstuck-mcp
Prevents GitHub Copilot CLI coding agents from repeatedly attempting the same failed fix by tracking attempts and blocking further fixes until a web search is performed.
Prevents OpenAI Codex CLI coding agents from repeatedly attempting the same failed fix by tracking attempts and blocking further fixes until a web search is performed.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@unstuck-mcpreport a failed fix attempt for the login error"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
unstuck-mcp
Stops coding agents from looping on the same failed fix. Tracks failed attempts per-problem, and once the same error has been "fixed" a couple of times without success, it blocks further fixes until the agent actually uses its own web search tool — instead of guessing again from stale memory.
Works with GitHub Copilot CLI, OpenAI Codex CLI, and OpenCode, because
all three speak MCP, all three read AGENTS.md, and all three already ship a
web search tool of their own. This server doesn't duplicate that search — it
just gates on whether it happened.
How it works
The agent calls
report_attempt(error_signature, fix_summary)after any failed fix.The server normalizes the error text (strips line numbers, file paths, quoted values) and hashes it, so near-identical failures are recognized as "the same problem" even if the wording drifts slightly.
On the 3rd attempt at the same normalized problem (configurable), the tool response tells the agent it's blocked: it must use its own web search tool before trying anything else.
Once it has searched, the agent calls
confirm_search(error_signature, findings_summary). This clears the block and resets the attempt count for that problem, informed by what it just found.If the agent tries another fix while still blocked (i.e. it skipped the search),
report_attemptcalls it out explicitly instead of quietly logging it.
This is enforced through instructions, not a hard runtime block — MCP servers
can't intercept an agent's other tool calls the way an editor plugin can. It
works because the tool descriptions and the bundled AGENTS.md rule make
calling it the obvious, expected thing to do, the same pattern that made
docs-lookup MCP servers like Context7 stick. confirm_search closes the loop:
the agent can't just claim it's unblocked without a tool call that says so.
Related MCP server: ContextEngine
Install
cd unstuck-mcp
npm installThen wire it into whichever CLI(s) you use:
GitHub Copilot CLI
copilot mcp add
# Command: node
# Args: /absolute/path/to/unstuck-mcp/index.jsor edit ~/.copilot/mcp-config.json directly:
{
"mcpServers": {
"unstuck": {
"command": "node",
"args": ["/absolute/path/to/unstuck-mcp/index.js"]
}
}
}OpenAI Codex CLI
Add to your Codex config (~/.codex/config.toml):
[mcp_servers.unstuck]
command = "node"
args = ["/absolute/path/to/unstuck-mcp/index.js"]OpenCode
Add to opencode.json (project or global):
{
"mcp": {
"unstuck": {
"type": "local",
"command": ["node", "/absolute/path/to/unstuck-mcp/index.js"],
"enabled": true
}
}
}Enable the enforcement rule
Copy the contents of AGENTS.snippet.md into your project's AGENTS.md
(all three tools read this file). Without it, the agent still can call these
tools, but won't reliably choose to on its own.
Configuration
Environment variables (set them in the MCP server config's env block):
Variable | Default | Purpose |
|
| How many failed attempts before blocking (3rd attempt = 1st time blocked) |
|
| Where attempt history is stored |
Tools exposed
report_attempt(error_signature, fix_summary)— log a failed attempt, get back whether you're blockedconfirm_search(error_signature, findings_summary)— clear a block after actually searchingloop_status()— see everything currently tracked as stuck, for debuggingreset_loop(error_signature?, clear_all?)— clear history manually
Known limitation
This relies on the agent following its instructions honestly — calling
report_attempt after failures, and not calling confirm_search without
actually searching. It's not a hard sandbox-level block like an OpenCode
plugin hook could be. In exchange, it works identically across every
MCP-compatible agent instead of being locked to one tool's plugin architecture,
and it doesn't duplicate a search tool the agent already has.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- Alicense-qualityFmaintenanceDetects and breaks repetitive fix loops in AI coding assistants by tracking attempts and providing escalating intervention strategies. It utilizes error fingerprinting and similarity analysis to redirect the AI toward new approaches when it gets stuck on the same error.Last updated164MIT

ContextEngineofficial
AlicenseAqualityAmaintenancePersistent memory and mechanical enforcement for AI coding agents — so they stop repeating your mistakes.Last updated21273Business Source 1.1- Alicense-qualityDmaintenanceAn MCP server for detecting retry loops and analyzing iteration patterns in agentic coding workflows, providing structured debugging intelligence to improve repair attempts.Last updated5MIT
- Alicense-qualityAmaintenanceLocal-first error memory for AI coding agents, enabling them to search past fixes before attempting new repairs and save verified cases as Markdown.Last updatedMIT
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