AppSignal MCP Server
mcp-appsignal
Ein MCP-Server (Model Context Protocol) zum Verbinden mit AppSignal und Abrufen von Vorfallinformationen.
Installation
npm install -g mcp-appsignalRelated MCP server: Sentry MCP Server
Verwendung
Befehlszeile
# Set environment variables
export APPSIGNAL_API_TOKEN=your-api-token
export APPSIGNAL_APP_ID=your-app-id
# Run the server
mcp-appsignalMit Cursor
Fügen Sie zu Ihren Cursoreinstellungen hinzu:
{
"mcp": {
"servers": {
"appsignal": {
"command": "npx",
"args": ["mcp-appsignal"],
"env": {
"APPSIGNAL_API_TOKEN": "your-api-token",
"APPSIGNAL_APP_ID": "your-app-id"
}
}
}
}
}Merkmale
Stellen Sie eine Verbindung zur GraphQL-API von AppSignal her
Holen Sie sich Vorfalldetails und Beispiele
Vorfälle auflisten und suchen
Geben Sie Eingabeaufforderungen zur Analyse von Vorfällen und zum Vorschlagen von Korrekturen an
MCP-Ressourcen
appsignal://incident/{incidentNumber}– Details zu einem bestimmten Vorfall abrufenappsignal://incident/{incidentNumber}/sample/{sampleId?}– Holen Sie sich ein Beispiel für einen bestimmten Vorfallappsignal://incidents- Alle Vorfälle auflisten
MCP-Tools
getIncident- Einen Vorfall nach Nummer abrufengetIncidentSample– Ruft ein Beispiel für einen bestimmten Vorfall ablistIncidents– Vorfälle mit optionaler Filterung auflisten
MCP-Eingabeaufforderungen
analyzeIncident- Analysieren Sie einen Vorfall und liefern Sie ErkenntnissesuggestFixes– Schlagen Sie Korrekturen für einen Fehler vor
Lizenz
MIT
Available Tools
3 toolsgetIncidentD
| Name | Required | Description | Default |
|---|---|---|---|
| incidentNumber | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
getIncidentSampleD
| Name | Required | Description | Default |
|---|---|---|---|
| incidentNumber | Yes | ||
| sampleId | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listIncidentsD
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| state | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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?
Tool has no description.
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.
3 tool updates
v1.0.0- First observed
getIncident - First observed
getIncidentSample - First observed
listIncidents
TDQS
Scored across 3 tools
The tools have distinct names (getIncident, getIncidentSample, listIncidents) suggesting different purposes, but without descriptions, it's unclear how 'getIncident' and 'getIncidentSample' differ—they could overlap in retrieving incident data. The 'listIncidents' is clearly separate for listing multiple incidents.
All tool names follow a consistent camelCase pattern with clear verb-noun combinations (getIncident, getIncidentSample, listIncidents). There are no deviations in naming style, making them predictable and readable.
With only 3 tools, the server feels thin for an incident management domain, as it likely lacks essential operations like creating, updating, or resolving incidents. This minimal set may not support complete agent workflows, indicating an under-scoped tool surface.
Inferred from the domain (incident management), there are significant gaps: no tools for creating, updating, deleting, or resolving incidents, and no coverage for related entities like alerts or metrics. This incomplete surface will likely cause agent failures in handling full incident lifecycles.
Maintenance
Related MCP Connectors
Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.
Model Context Protocol server for the Apideck Unified API. Connect any MCP-compatible agent framework to 100+ accounting systems, HRIS platforms, file storage providers, and more through one integration. More information https://www.apideck.com/mcp-server
Model Context Protocol server for Studex tools, notifications, and profile integrations
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
Related MCP Servers
- FlicenseBqualityDmaintenanceA Model Context Protocol server that retrieves and analyzes Sentry.io issues, allowing users to inspect error reports, stacktraces, and debugging information from their Sentry account.222-

Sentry MCP Serverofficial
FlicenseBqualityFmaintenanceA Model Context Protocol server that lets AI assistants interact with the Sentry API to retrieve and analyze error data, manage projects, and monitor application performance.1112-- AlicenseBqualityDmaintenanceA Model Context Protocol (MCP) server that enables interaction with Waroom API to retrieve incident information and postmortem details through a standardized protocol.2616 npm1MIT

DevRev MCP Serverofficial
AlicenseBqualityNot gradedmaintenanceA Model Context Protocol server that enables searching, retrieving, creating, and updating issues and tickets using DevRev APIs.1610MIT