Snapback is a remote MCP server that gives an AI agent 23 tools, among them agent_memory, budget_guard, cascade_root. It answers at https://api.snapback.sh/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 4 of 4 times since 23 September 2026; the last check, on 7 November 2026, succeeded.
Diagnose why an AI agent failed and get the verified fix instantly. Free, no token.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
agent_memory | See what YOU (this agent) tend to fail on — your recurring failure patterns across past diagnoses. Returns your top failure classes with counts and what share of your failures each is (e.g. 'loop_repeated_tool_call: 12 times, 40%'). Call it Inputs: limit |
budget_guard | Live MID-RUN budget check (fast, no LLM). Send whatever counters you have and get an advisory on context %, token burn, cost burn, step budget, and off-task drift - with concrete suggested_actions and the projected cost of NOT acting. Call Inputs: step, max_steps, tokens_used, token_budget, cost_used_usd, cost_budget_usd |
cascade_root | Given an ORDERED list of errors from a run (oldest first), find the TRUE root — the error that cascaded or shouldn't have been retried — not just the final symptom you see. E.g. a 429 that got retried and triggered a downstream 401: the roo Inputs: errors |
convert_trace | Turn your raw logs into a Snapback trace so you don't hand-craft JSON. Pass 'source' = a list of log/step entries, or an object with a spans/steps/messages/events/logs array (OTel spans, OpenAI/LangChain message lists, or generic {tool,inpu Inputs: source, hint |
detect_loop | MID-RUN loop check (fast, no LLM, free). Send your recent steps DURING a run; get back whether you're stuck repeating a tool call and a concrete next move. Call this every few steps to catch a loop BEFORE you burn your step budget — don't w Inputs: steps, threshold |
diagnose_batch | Diagnose SEVERAL traces in one call (up to 20). Each trace is metered like a separate diagnose_trace. Returns a verdicts array (per-trace, order preserved); a bad trace in the batch is isolated and doesn't fail the rest. Use for post-run an Inputs: traces |
diagnose_infra_error | Diagnose a cryptic AGENT-INFRASTRUCTURE error — payments (x402/EIP-3009), Solana on-chain (ATA, blockhash, compute), MCP protocol, RPC/providers, EVM & Solana wallets, library of VERIFIED fixes the base model often gets wrong. Pass the erro Inputs: error, context, action, format |
diagnose_trace | Diagnose why an AI agent run failed. Returns a structured verdict (failure_class, failed_at_step, root_cause, fix_suggestion, confidence). LATENCY: known patterns return library-instant (<1s); a NOVEL failure needs an LLM call and can take Inputs: trace |
get_request_status | Check what happened to a pattern you requested (from request_pattern's request_id). Returns pending / approved / rejected / in_library so you can see if your suggestion was actioned — the feedback loop isn't a black box. Free, no token. Inputs: request_id |
get_verdict | Fetch a previously produced verdict by its id or by trace_id (your org only). Inputs: verdict_id, trace_id |
my_impact | See how your feedback + pattern requests have shaped the shared library — how many verdicts you've rated, patterns you've requested, and how many were approved into the library. Turns your input into visible collaboration. Token-scoped to y |
my_usage | See YOUR current usage + remaining allowance so you can self-govern spend: snapbacks (diagnoses) used/cap/remaining, guard checks used/cap/remaining, estimated spend, % used, and when it resets. Call it periodically to avoid surprises. Toke |
preflight | BEFORE running: get known failure patterns for a given agent setup so you can avoid them. Returns a ranked list of {failure_class, root_cause, fix_suggestion} from Snapback's library. Call this before executing a plan and self-correct. Inputs: agent_stack, tags, limit |
recommend_failover | Should you RETRY the same target, SWITCH provider, FALL BACK to another chain, or STOP? Pass the error + your configured topology (current_chain, available_chains, and/or current_provider, available_providers) and get deterministic routing Inputs: error, current_chain, available_chains, current_provider, available_providers |
report_outcome | Report the outcome of an auto-applied fix (the self-heal interceptor calls this after it gate-applied a fix and retried). Pass failure_class, family, fix, confidence, action_class, and succeeded (did the retry work?). TWO purposes: it's you Inputs: failure_class, family, fix, confidence, action_class, succeeded |
request_pattern | Leave us a message: ask us to add a failure pattern to the library, or report a problem we couldn't diagnose well. Use this when diagnose_trace didn't have a good answer, when you keep hitting a failure we don't classify, or when you want a Inputs: message, kind, verdict_id, context |
search_docs | Search Snapback's documentation for how to use it — how to format a trace, what each tool does, the failure taxonomy, auth, pricing, and errors. Free and needs no token. Call this first if you're unsure how to format a request or what a ver Inputs: query, limit |
session_end | Close a live session and get a short run summary (total steps, duration). Frees the session. Free, no token. Inputs: session_id |
session_start | Open a LIVE mid-run session so Snapback can watch your run step-by-step and warn you in real time (loop / token / cost / context) - the always-on guardian mode. Returns a session_id. Free, no token. Call session_step as you run, session_end Inputs: agent_id |
session_step | Report ONE step of a live run and get back any warnings immediately (loop detected / budget breach). Pass the step (action + inputs) and any counters you have (step, max_steps, tokens_used, token_budget, cost_used_usd, cost_budget_usd, cont Inputs: session_id, step, counters, loop_threshold |
submit_feedback | Tell Snapback whether a verdict was correct (correct=true/false), with an optional free-text note (did the fix work? what was wrong?). ONE rating per verdict — call it AFTER you act on a verdict and see the outcome. Your correction updates Inputs: verdict_id, correct, note |
suggest_budget_recovery | Approaching a token/context/cost budget mid-run? Pass your counters and get the LEAST-DISRUPTIVE recovery ranked: truncate context | switch to a cheaper model | batch steps | wrap up — scored by speed gained, accuracy lost, cost saved. Turn Inputs: tokens_used, token_budget, context_used, context_window, cost_used_usd, cost_budget_usd |
what_others_did | THE CROWD: for a failure_class (or pass the family/error and we'll map it), see what OTHER agents did about the same failure and whether it worked — anonymized, aggregated across everyone. Returns {total, agree_pct (community success rate), Inputs: failure_class, error |
Every block below points at https://api.snapback.sh/mcp. Pick your client and copy.
claude mcp add --transport http snapback https://api.snapback.sh/mcp
{
"mcpServers": {
"snapback": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://api.snapback.sh/mcp"]
}
}
}{
"mcpServers": {
"snapback": {
"url": "https://api.snapback.sh/mcp"
}
}
}{
"servers": {
"snapback": {
"type": "http",
"url": "https://api.snapback.sh/mcp"
}
}
}{
"context_servers": {
"snapback": {
"url": "https://api.snapback.sh/mcp"
}
}
}{
"mcpServers": {
"snapback": {
"serverUrl": "https://api.snapback.sh/mcp"
}
}
}{
"mcpServers": {
"snapback": {
"url": "https://api.snapback.sh/mcp"
}
}
}name: Snapback
version: 0.0.1
schema: v1
mcpServers:
- name: Snapback
type: streamable-http
url: https://api.snapback.sh/mcp{
"mcpServers": {
"snapback": {
"httpUrl": "https://api.snapback.sh/mcp"
}
}
}{
"mcpServers": {
"snapback": {
"type": "http",
"url": "https://api.snapback.sh/mcp"
}
}
}{
"mcpServers": {
"snapback": {
"url": "https://api.snapback.sh/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fapi.snapback.sh%2Fmcp&type=streamable_http&id=snapback&name=Snapback
It answered our last check on 7 November 2026 in 555 ms. Over 4 checks since 23 September 2026 it answered 4. Status here comes from Neuronto's own probes, not from the publisher.
23, as returned by the server's own tools/list on 12 November 2026: agent_memory, budget_guard, cascade_root, convert_trace, detect_loop, diagnose_batch, diagnose_infra_error, diagnose_trace, and 15 more.
It answered our last check on 7 November 2026 in 555 ms. Over 4 checks since 23 September 2026 it answered 4.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://api.snapback.sh/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: io.github.ra1labsworkx-wq. Endpoint host: api.snapback.sh. ARD identifier: urn:air:io.github.ra1labsworkx-wq:mcp:snapback.
First indexed 21 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.