Exposes live LLM pricing comparisons through five tools: get_pricing for real-time GNK/USD rates and per-million-token costs, compare_providers to benchmark against OpenAI/Anthropic/DeepSeek, calculate_savings to estimate monthly and annual cost reductions based on current spend, get_available_models for listing inference options, and get_signup_link for referral-enabled registration. Pricing data refreshes every 10 minutes from Gonka's API, with competitor rates pulled daily from LiteLLM's database. Useful when evaluating inference cost optimization or building cost-aware agent workflows. Works over streamable HTTP, so you can call it from Claude Desktop, the Python MCP SDK, fastmcp CLI, or raw curl with session headers.
Public tool metadata for what this MCP can expose to an agent.
get_pricingGet current Gonka Network pricing data. Returns live pricing including: - Cost per 1M tokens in USD and GNK - Current GNK/USD exchange rate - Comparison ratios vs OpenAI, Anthropic, DeepSeek - $50 deposit example: how many tokens you get - Data freshness timestampGet current Gonka Network pricing data. Returns live pricing including: - Cost per 1M tokens in USD and GNK - Current GNK/USD exchange rate - Comparison ratios vs OpenAI, Anthropic, DeepSeek - $50 deposit example: how many tokens you get - Data freshness timestamp
No parameter schema in public metadata yet.
get_available_modelsList models available on Gonka Network. Returns each model's: - ID (same as used in OpenAI API calls) - Availability status (available / restricted) - Notes on access requirementsList models available on Gonka Network. Returns each model's: - ID (same as used in OpenAI API calls) - Availability status (available / restricted) - Notes on access requirements
No parameter schema in public metadata yet.
compare_providersCompare Gonka Network pricing against a competitor.1 paramsCompare Gonka Network pricing against a competitor.
providerstringcalculate_savingsCalculate how much you would save by switching from OpenAI to Gonka Network.1 paramsCalculate how much you would save by switching from OpenAI to Gonka Network.
monthly_spend_usdnumberget_signup_linkGet the Gonka Network signup link with referral bonus. Returns the registration URL, welcome bonus details, and quick-start code snippet for connecting with the OpenAI SDK.Get the Gonka Network signup link with referral bonus. Returns the registration URL, welcome bonus details, and quick-start code snippet for connecting with the OpenAI SDK.
No parameter schema in public metadata yet.
All-in-one MCP server for Gonka Network: live pricing, cost comparisons, AI model recommendations, and access to complete technical documentation via knowledge graph search.
Helps AI agents and developers:
Live at: https://mcp.gogonka.com/mcp
Add to your claude_desktop_config.json:
{
"mcpServers": {
"gonka-pricing": {
"url": "https://mcp.gogonka.com/mcp"
}
}
}
Restart Claude Desktop. The server will appear in Claude's available tools.
# Test the server
curl -X POST https://mcp.gogonka.com/mcp \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","method":"tools/list","id":1}'
Two sides of one mission:
get_pricing for the live number (refreshed every 10 minutes)get_pricing)get_pricing() — No parametersGet live Gonka Network pricing and comparisons.
Returns:
Next: Call calculate_savings() to show exact annual savings.
calculate_savings(monthly_spend_usd: 0.01–1,000,000 = 100.0)Calculate exact savings from switching to Gonka.
Returns:
Example: $500/month OpenAI → save ~$5,000/year
get_available_models() — No parametersList models available on Gonka Network with pricing (cost per 1M tokens, status).
Recommended model: MiniMaxAI/MiniMax-M2.7 (live $/1M tokens in the response)
compare_providers(provider: openai | anthropic | deepseek | mistral | gemini = openai)Compare Gonka Network pricing vs a competitor.
Returns:
Example: returns the live "Gonka is cheaper by N×" ratio for the chosen provider
suggest_model_for_task(task_description: str, monthly_budget_usd: 0–1,000,000 = 0, current_provider: openai | anthropic | deepseek | mistral | gemini = openai)Suggest the best and cheapest model for a specific task.
Parameters:
task_description (required): What the model should domonthly_budget_usd: Current monthly API spend (0 = unknown)current_provider: Current provider for comparisonReturns:
get_signup_link() — No parametersGet Gonka Network signup URL and integration guide.
Returns:
get_trial_key() — No parametersIssue a free trial key instantly — no registration, no credit card.
Returns:
gc- API key, 100K tokens, 10 req/min, OpenAI-compatible base_urlNote: expires in 2 hours unless used; the first inference call extends it to 24 hours. One key per IP per 24h (idempotent). HTTP transport only — not available when the server is run over stdio.
register_on_gonka(monthly_spend_usd: number = 100.0, current_provider: str = "openai", user_query: str = "")Get a personalized cost-analysis pitch and signup link. Does not create an account — it only computes savings and returns the signup URL; registration itself happens at that URL.
Search and explore Gonka Network's technical knowledge base — 1000+ concepts including architecture, concepts, FAQ, tutorials, and troubleshooting.
query_graph(question: str, depth: int = 3, token_budget: int = 2000)Search the knowledge graph by topic. Returns relevant nodes and relationships with context.
Example queries:
Returns: List of matching concepts, relationships, document excerpts
get_node(label: str)Get detailed information about a specific concept node.
Example: get_node("Distributed Key Generation (DKG)") returns definition, relationships, related documents.
get_neighbors(label: str, relation_filter: str = "")Find concepts directly connected to a given concept, with relation type and confidence for each edge. Optionally filter by relation substring.
Use case: User understands concept A, show them related concepts to deepen knowledge.
get_god_nodes()Get high-level overview — the most central and important concepts in the Gonka knowledge graph.
Returns: Architecture, Consensus, Governance, DKG, Bridge, Economic Model, etc.
get_graph_stats()Get statistics about the knowledge graph: total nodes, communities, edges, last update time.
get_community(community_id: int)Get all concepts in a specific knowledge community (e.g., "FAQ", "Architecture", "Operations").
find_shortest_path(source: str, target: str, max_hops: int = 8)Find the shortest conceptual path between two ideas.
Example: Shortest path from "GNK Coin" to "Ethereum Bridge" — shows intermediate concepts.
search_docs(query: str, max_results: int = 3, context_chars: int = 400)Full-text search across all documentation files — every word in query must appear in a file (AND search). Use when query_graph returns nothing.
read_doc(filename: str, max_chars: int = 8000)Read the full text of a specific documentation file, including code examples and commands.
Use case: Get the complete article instead of just search results.
list_docs()List all available documentation filenames.
Agents can use these built-in prompts to start conversations:
gonka_start(task: string = "general LLM inference")Seeds a cost-comparison conversation for a given task, with live price/ratio.
calculate_my_savings(monthly_spend_usd: string = "100")Seeds a savings-estimate conversation against current OpenAI/Anthropic spend.
gonka://pricing-guideStructured pricing data, decision matrix, deposit examples, API snippets.
Updated every 10 minutes from live sources.
from openai import OpenAI
client = OpenAI(
base_url="https://gate.joingonka.ai/v1",
api_key="your_gonka_api_key"
)
response = client.chat.completions.create(
model="MiniMaxAI/MiniMax-M2.7",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://gate.joingonka.ai/v1",
apiKey: process.env.GONKA_API_KEY,
});
const response = await client.chat.completions.create({
model: "MiniMaxAI/MiniMax-M2.7",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);
OPENAI_BASE_URL=https://gate.joingonka.ai/v1
OPENAI_API_KEY=your_gonka_api_key_here
Gonka's price per 1M tokens is set in GNK, so the USD price and every "cheaper by N×" ratio float with the GNK/USD exchange rate. Numbers printed in a README go stale by design — always get them live:
get_pricing tool → current $/1M tokens, GNK/USD rate, ratios vs OpenAI/DeepSeekcompare_providers tool → side-by-side vs openai / anthropic / deepseek / mistral / geminiAt recent rates Gonka has been three to four orders of magnitude cheaper than GPT-4o per token.
Because the ratio is so large, switching saves approximately your entire
current bill: $100/month on OpenAI → roughly $1,200/year saved
(use calculate_savings(monthly_spend_usd=...) for exact live numbers).
Flow 1: Cost Optimization (user cares about price)
get_pricing()calculate_savings(user_spend)suggest_model_for_task(user_task)get_signup_link()Flow 2: Technical Deep Dive (user cares about architecture)
query_graph("Gonka architecture network")get_god_nodes()get_node(topic) or read_doc(filename)get_neighbors(label)find_shortest_path(concept_a, concept_b)Flow 3: Combined (technical validation before switching)
get_trial_key (idempotent but not read-only — it creates a key)get_trial_key is the one exception (creates a rate-limited trial key, non-destructive)Live health grade: https://wmcp.sh/mcp/grade/mcp.gogonka.com (check the page for the current score — it changes over time)
This server is indexed and periodically scanned by several third-party MCP directories and quality graders (e.g. wmcp.sh, agent-tools.cloud); exact scan frequency is set by those services, not by us.
https://mcp.gogonka.com/mcpQ: Will my code break switching from OpenAI?
A: No. Change 2 lines:
# Before
client = OpenAI(api_key="sk-...")
# After
client = OpenAI(
base_url="https://gate.joingonka.ai/v1",
api_key="gonka_key_..."
)
Q: What's the catch?
A: None. Gonka uses spare GPU capacity on blockchain validators — lower overhead = lower costs for customers.
Q: Is Gonka as good as OpenAI?
A: Different use case. MiniMax-M2.7 works well for most chat/code tasks. For cutting-edge research, OpenAI GPT-4o is still better — but costs thousands of times more per token.
Q: Can I use with LangChain?
A: Yes:
from langchain.llms import OpenAI
llm = OpenAI(
openai_api_base="https://gate.joingonka.ai/v1",
openai_api_key="gonka_key_..."
)
Q: Support & Status?
A: https://wmcp.sh/mcp/grade/mcp.gogonka.com (A-grade goal) | info@gogonka.com
License: MIT
Version: 2.1.0 (audit fixes: trial-key conversion fields, AND doc search, actionable errors, rate-proof docs, README synced to the actual 18-tool/2-prompt surface, dead A2A badge removed)
Last Updated: July 16, 2026
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