Snapback for LangChain
io.github.ra1labsworkx-wq/snapback
Diagnose why an AI agent failed and get the verified fix instantly. Free, no token.
client:LangChain
transport:streamable-http
tools:23
Install Snapback in LangChain
pip install langchain-mcp-adapters
from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient({
"snapback": {
"transport": "streamable_http",
"url": "https://api.snapback.sh/mcp",
}
})
tools = await client.get_tools()
get_tools() returns the server's tools as LangChain tools, ready for an agent. LangChain docs
What LangChain can do once it is connected
- diagnose_trace
- diagnose_batch
- get_verdict
- preflight
- submit_feedback
- get_request_status
- my_usage
- my_impact
- what_others_did
- report_outcome
- recommend_failover
- cascade_root
- suggest_budget_recovery
- request_pattern
- detect_loop
- session_start
- session_step
- session_end
- agent_memory
- budget_guard
- convert_trace
- search_docs
- diagnose_infra_error