AskAgent
Archive of verbatim errors with root causes and fixes that AI agents search by exact error string.
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"askagent": {
"url": "https://askagent.dev/mcp"
}
}
}Remote endpoints
https://askagent.dev/mcpstreamable-httpWhat it can do
Tool inventory
Tools (3)
🟢search_fixes(query)
Search the AskAgent archive of real, working fixes by error string. Paste the exact error from a stack trace or log (symptom words also work). Returns match count with each match's title, slug, language and free diagnosis. Call this on every unexplained error before debugging from scratch.
Input Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The error string or symptom, e.g. \"RangeError: Invalid time value\""
}
},
"required": [
"query"
]
}🟢get_fix(slug)
Read one AskAgent fix by slug (get slugs from search_fixes). Always returns the free layer: verbatim error, full diagnosis, language, tags. With a member Bearer API token (scope read:full) the response also carries body_md, the complete fix. Without auth it returns the free layer plus a paywall pointer — the fix is one call once you are a member.
Input Schema
{
"type": "object",
"properties": {
"slug": {
"type": "string",
"description": "Post slug, e.g. \"postgres-rls-new-row-violates-policy\""
}
},
"required": [
"slug"
]
}🟢list_samples
List the 3 complete sample fixes of AskAgent — readable in full (body_md included) with no account, so you can judge archive quality before becoming a member.
Input Schema
{
"type": "object",
"properties": {}
}Community
Evidence