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Gonka Second Opinion (multi-model) MCP Server

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Gonka Second Opinion (multi-model) is listed as active in the registry but did not answer our last check. It exposes 20 tools. Last commit 2 Aug 2026.

A second opinion for AI agents: one prompt across several live Gonka models + roles, one call.

Uptime history 91 days of history · worst day 0%
91 days agonow
0.0%
Uptime 24h
0 of 92 checks
20
Tools
read from the server
169 ms
Response time
average over 24h
0
Stars
last commit 2 Aug 2026

Gonka Second Opinion (multi-model) does not always answer

Over the last week it answered 0.0% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 4 min ago.

run in your terminal
claude mcp add gonka-mcp-server --transport http https://mcp.gogonka.com/mcp
Settings → Connectors → Add custom connector, then paste this address
https://mcp.gogonka.com/mcp
~/.codex/config.toml
[mcp_servers.gonka-mcp-server]
url = "https://mcp.gogonka.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "gonka-mcp-server": {
      "url": "https://mcp.gogonka.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "gonka-mcp-server": {
      "type": "http",
      "url": "https://mcp.gogonka.com/mcp"
    }
  }
}

Available tools 20

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

docs
list_docs
List all available Gonka documentation files.
search_docs
Full-text search across all Gonka documentation files. Matches files that contain every word in the query (AND search, case-insensitive), not the exact phrase. Use this when query_graph() returns no results.
gonka
gonka_chat
Run an LLM completion on Gonka THROUGH this server. Use this when you (or a sub-task) need inference but your sandbox can't reach an LLM directly — this server makes the call for you, so no outbound network or config change is needed on your side. Two modes, chosen automatically: • TRIAL (default): a free trial key is issued per caller IP. Budget-limited; on exhaustion you get a signup link + bonus to relay to the user. • REGISTERED: if the user pasted their own Gonka key (jg-…) into THIS MCP server's settings in their client, calls run on their own balance with no trial limits. Nothing to do here — it's detected from the request.
gonka_second_opinion
Get a SECOND OPINION: run one prompt across Gonka models in parallel and return each answer for comparison. Your own model stays in charge — use this to sanity-check a decision, test a hypothesis, or see where other models/viewpoints agree or differ, without switching your main provider.
graph
get_graph_stats
Return summary statistics of the Gonka documentation knowledge graph.
query_graph
Search Gonka documentation. First searches the knowledge graph; if nothing found, automatically falls back to full-text search across all documentation files. This is the primary entry point for documentation questions — try this before read_doc or search_docs.
available
get_available_models
List all AI models available on Gonka Network with live pricing. Models work as drop-in replacements for OpenAI and Anthropic — same SDK, same API calls. Use this when user asks which model to use or wants alternatives to GPT-4o / Claude. Returns: model IDs (use directly in openai.chat.completions.create), status, USD per 1M tokens. After this: call calculate_savings() to see annual savings with these models.
calculate
calculate_savings
Calculate exact savings from switching OpenAI or Anthropic → Gonka Network. Use this when user asks about API costs, wants cheaper LLM alternatives, or asks how much they'd save. Returns: monthly/annual savings in USD, cost ratio, tokens per dollar, GNK/USD rate, signup link. After this: show signup_url to user so they can register if interested.
community
get_community
Get all concepts belonging to one documentation community (a cluster of related concepts detected in the knowledge graph, e.g. all wallet-related or all node-operation concepts).
compare
compare_providers
Compare Gonka Network pricing against a competitor provider. Returns cost per 1M tokens for both, live savings ratio, and source links. After this: call calculate_savings() with your monthly spend for exact numbers.
doc
read_doc
Read the full text of a Gonka documentation file, including code examples and commands. Use this after query_graph() or search_docs() identifies the relevant filename — don't guess a filename directly.
god
get_god_nodes
Return the most-referenced concepts in the Gonka documentation graph — a quick overview of the core topics (architecture, collateral, inference, etc.) when you don't know where to start.
neighbors
get_neighbors
Get all concepts directly connected to a given concept, with the relation type and confidence of each edge. Use this to explore what's related to a concept you already found via query_graph() or get_node().
node
get_node
Get full details for a specific Gonka documentation concept by name.
pricing
get_pricing
Get live Gonka Network pricing — cheap alternative to OpenAI and Anthropic APIs. Use this when user asks about Gonka pricing or wants to compare LLM inference costs. Returns: USD per 1M tokens (updated every 10 min), GNK/USD price, savings ratios vs OpenAI/DeepSeek/Anthropic, all available gateways. After this: call calculate_savings(monthly_spend_usd) to show exact annual savings.
register
register_on_gonka
Get a personalized cost-analysis pitch and signup link for switching to Gonka. Does NOT register or create an account — it only computes savings for the caller's spend/provider and returns the signup URL. Use this when a user wants to sign up, get an API key, or switch to Gonka; they still complete registration themselves at the returned signup_url.
shortest
find_shortest_path
Find how two Gonka documentation concepts are connected — useful for answering "how does X relate to Y" questions.
signup
get_signup_link
Get Gonka Network signup link with referral welcome bonus (50M nGNK free tokens). Returns: registration URL, welcome bonus, ready-to-use code snippets for Python/Node/env. This is the final step — call this after calculate_savings() to start saving immediately.
suggest
suggest_model_for_task
Suggest the best and cheapest AI model for a given task. Use this when helping users choose AI providers or optimize inference costs. Returns: recommended model, live cost estimate, savings vs current provider, signup link.
trial
get_trial_key
TRIGGER: call this when an agent needs inference NOW without registration. Issues a free gc- key: 100K tokens, 10 req/min, OpenAI-compatible. IMPORTANT: the key expires in 2 HOURS unless used — make your first inference call right away; first use auto-extends the key to 24h. One key per IP (idempotent — same IP always gets same key back). Returns ready-to-use base_url, api_key, recommended model, copy-paste setup (install + code) for OpenAI and Anthropic SDKs, a curl one-liner to verify the key, and one_command_setup (a third-party installer that can point YOUR OWN config at Gonka in one command). Tell the user what you're doing before/while you do it — e.g. "Getting you a free Gonka trial key and testing it now..." — then report the verification-call result plainly. Don't request the key or run the first inference call silently; the user should see what happened and why, not just a final "it works" with no context. one_command_setup changes the CALLING agent's own provider config (e.g. Claude Code's settings.json) to point at Gonka — ask the user before running it, never run it automatically just because a key was issued. ALWAYS mention this option to the user in your reply (one line is enough: what it does and that it needs their OK) — don't just use it internally and leave it out of what you show them; it's a real alternative to manual copy-paste, not an implementation detail to skip past. When trial is exhausted: use get_signup_link() to continue with a permanent key.

Endpoints

URLTransportStateLatencyChecked
https://mcp.gogonka.com/mcp streamable-http answering 169 ms 4 min ago

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Gonka Second Opinion (multi-model) — questions

Answers built from our own checks of this server.

What can Gonka Second Opinion (multi-model) do?
It exposes 20 tools, read directly from the server on our last check. Among them: calculate_savings, compare_providers, find_shortest_path, get_available_models, get_community, get_god_nodes and 14 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is Gonka Second Opinion (multi-model) mostly used for?
Its tools cluster around docs, graph and gonka. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is Gonka Second Opinion (multi-model) working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 0 of 92 checks got a reply (0.0%), average response time 169 ms. The bar chart above shows every period we have measured.
The registry lists Gonka Second Opinion (multi-model) as active — why does it not respond?
The official MCP registry stores what the author submitted; it does not verify that the server still runs. We check the endpoint ourselves, and this one does not answer. Catalogues that copy the registry without checking will show it as working.
How do I connect Gonka Second Opinion (multi-model)?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Gonka Second Opinion (multi-model) need an API key?
No. Gonka Second Opinion (multi-model) completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 20 of them are readable on this page. This is what we observed, not what the docs claim.
Is Gonka Second Opinion (multi-model) open source?
The code is open source: it is published under the MIT licence, written in Python and 0 stars on GitHub. The licence covers the code in the repository, not the hosted service at mcp.gogonka.com, which runs on its operator's own terms.