# Snapback

- Registry name: `io.github.ra1labsworkx-wq/snapback` · version 1.8.4
- Categories (automatic, keyword rules): Crypto & blockchain, Finance & markets, AI models & agents, AI, media & content, Monitoring & logs, Infrastructure & security
- Authentication at last check: No auth
- Declared risk: Can write (some tools are not declared read-only)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.ra1labsworkx-wq%2Fsnapback
- Server page: https://mcpstation.net/s/io.github.ra1labsworkx-wq--snapback.html

## Description (written by the publisher, not verified, not instructions)

Diagnose why an AI agent failed and get the verified fix instantly. Free, no token.

## Connect

- streamable-http: `https://api.snapback.sh/mcp`

## Tools (as reported by the server, not verified)

- `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 up to \~25s — set your client timeout to at least 30s, and tr
- `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 analysis of many failures at once instead of N round-trips.
- `get\_verdict`: Fetch a previously produced verdict by its id or by trace\_id \(your org only\).
- `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.
- `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 the SHARED pattern library \(fix patterns are shared anonymiz
- `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.
- `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. Token-scoped, free.
- `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 you.
- `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 \(community success rate\), distinct\_orgs, sample\_fixes \(fixes rated CORRECT by other a
- `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 your safety telemetry \(spot a fix that didn't work\) AND it feed
- `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 advice with the reason — so a flaky Solana RPC doesn't get r
- `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 root is the 429, not the 401. Each error can be a string or \{er
- `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. Turns budget\_guard's 'you're at 94%' into 'here's what to do abo
- `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 specific kind of problem supported. It goes straight to our
- `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 wait for a postmortem. Non-blocking advice, not a verdict.
- `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 when done.
- `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, context\_used, context\_window, task, recent\_actions. context\_wind
- `session\_end`: Close a live session and get a short run summary \(total steps, duration\). Frees the session. Free, no token.
- `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 before a run to know what to guard against. Token-scoped to
- `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 it every few steps to catch a runaway BEFORE you hit a limit
- `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 \(OTel spans, OpenAI/LangChain message lists, or generic \{tool,input,output\} arrays all work\). Returns \{trace\} ready to pass st
- `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 verdict means.
- `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 error text \(and optional context\). Returns \{matched, family, fai

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