gripe-mcp
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., "@gripe-mcpLog an issue: the 'plot' tool documentation is missing parameter descriptions."
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.
gripe-mcp
Agent complaint box — one-tool MCP for logging bugs and improvement requests.
One tool: report_issue
Call it when you guess, hit a missing tool, find bad docs, or produce uncertain output. Non-blocking — log and continue.
Param | Type | Description |
| str | What went wrong or what you'd like improved (max 200 chars) |
|
| low = friction, medium = guessed, high = abandoned/wrong |
| str | Which instruction or tool caused the issue (max 80 chars) |
| enum |
|
Related MCP server: semfora-error-reporter
Storage
Postgres: set
GRIPE_DB_URLenv var → singlegripe_issuestableJSONL fallback: timestamped files in
.gripe-mcp/(one per day)
Identity
GRIPE_AGENT_ID and GRIPE_TASK_ID are set at server startup via env vars.
The agent never self-reports identity.
System prompt block
## Self-Monitoring
Use `report_issue` any time you guess, hit a missing tool, or produce output
you're uncertain about. Non-blocking — log and continue, no response expected.
There is no penalty for logging; silence is the failure mode we're trying to
prevent.Run
GRIPE_AGENT_ID=precis GRIPE_TASK_ID=review-123 gripeAvailable Tools
1 toolreport_issueA
Report a bug, confusion, bad documentation, or improvement idea.
Call this when you:
had to guess or weren't confident in your output
hit a missing tool or capability
found unclear, wrong, or incomplete tool documentation
encountered ambiguous instructions
want to suggest a new tool, workflow step, or prompt fix
Non-blocking — log and continue your task. No response expected. There is no penalty for logging; silence is the failure mode.
description: what went wrong or what you'd like improved (max 200 chars) severity: low (friction) | medium (had to guess/workaround) | high (abandoned/wrong output) section: which instruction or tool caused the issue (max 80 chars) mode: ambiguous_instruction | missing_tool | bad_tool_doc | hallucination_risk | wrong_scope | memory_miss | other
| Name | Required | Description | Default |
|---|---|---|---|
| description | Yes | ||
| severity | No | low | |
| section | No | ||
| mode | No | other |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool is non-blocking, logs and continues the task, and that silence is the failure mode. It does not detail side effects like persistent storage, but for a logging tool this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a clear purpose, followed by a well-formatted bullet list of when to use, a behavioral note, and parameter definitions. Every sentence is necessary and efficiently conveys information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's purpose (logging issues), the description covers all essential aspects: usage triggers, behavior, parameter constraints, and output expectations (none). It is fully self-contained and eliminates the need for additional clarifications.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates fully by defining each parameter: description (max 200 chars), severity (with options low/medium/high), section (max 80 chars), and mode (with enum values). It also indicates defaults, making the schema's bare types actionable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is for reporting bugs, confusion, bad documentation, or improvement ideas. It uses a specific verb 'report' and resource 'issue', and distinguishes use cases via bullet points, making its purpose unmistakable even without sibling context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly lists when to call the tool (e.g., when guessing, missing tool, unclear docs, ambiguous instructions) and provides guidance on its non-blocking nature, lack of expected response, and absence of penalty. This leaves no ambiguity about appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v0.1.2- First observed
report_issue
TDQS
Only one tool exists, so there is no possibility of confusion. The purpose is clearly distinct.
A single tool follows a clear verb_noun pattern (report_issue), so consistency is perfect.
With only one tool, the server feels very thin. Even for a focused reporting utility, a single tool is minimal and limits usefulness.
The tool covers its stated purpose (reporting issues) with detailed fields. For a single-purpose server, completeness is high, though there are no auxiliary tools.
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 Connectors
- SuperlogOAuthsh.superlog
Open-source agent that observes and fixes your application. Query logs, traces, metrics, incidents.
Capture feature requests and bug reports from chat into a searchable, AI-categorized backlog.
Lints + auto-fixes how AI coding agents discover any new product. 24 rules, 6 tools, score 0-100.
Browser-backed QA with evidence and fix-ready reports for coding agents.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenancePersistent activity journal for AI agents - enables logging and querying decisions, changes, errors, and observations across sessions.131MIT

semfora-error-reporterofficial
FlicenseNot gradedqualityDmaintenanceProvides tools for logging, confirming, and triaging issues with the semfora-engine, enabling AI agents to report bugs discovered during workflows.-- AlicenseNot gradedqualityDmaintenanceTracks and analyzes AI agent tool calls with event logging, dashboard, per-tool and per-agent analytics, and error monitoring.MIT
- AlicenseBqualityAmaintenanceSelf-hosted issue tracker built for agent-driven development. One binary, SQLite storage, MCP-native, with a web UI, REST API, and CLI for the humans.2745Apache 2.0
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/retospect/gripe-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server