Server data from the Official MCP Registry
Compare LLM inference costs vs OpenAI/Anthropic/DeepSeek. Gonka is up to 6800x cheaper.
Compare LLM inference costs vs OpenAI/Anthropic/DeepSeek. Gonka is up to 6800x cheaper.
Remote endpoints: streamable-http: https://mcp.gogonka.com/mcp
This is a well-structured MCP server for exposing Gonka Network pricing data with appropriate security controls. Authentication is not required (pricing data is public), and the server has no dangerous patterns, malicious code, or sensitive credential handling. Permissions are narrowly scoped to file I/O and network requests appropriate for a pricing lookup service. Minor code quality observations do not materially impact security. Supply chain analysis found 5 known vulnerabilities in dependencies (1 critical, 3 high severity).
3 files analyzed · 10 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
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() — 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 ($0.000325/1M tokens)
compare_providers(provider: openai | anthropic | deepseek | mistral | gemini = openai)Compare Gonka Network pricing vs a competitor.
Returns:
Example: Gonka vs OpenAI = 7,681× cheaper
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:
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(node_id: str)Find related concepts and topics connected to a given node.
Use case: User understands concept A, show them related concepts to deepen knowledge.
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.
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").
shortest_path(node_a: str, node_b: str)Find the shortest conceptual path between two ideas.
Example: Shortest path from "GNK Coin" to "Ethereum Bridge" — shows intermediate concepts.
read_doc(doc_id: str)Read the full text of a specific documentation file.
Use case: Get complete article instead of just search results.
list_docs()List all available documentation files with summaries.
Agents can use these built-in prompts to start conversations:
find_cheapest_api(task: string = "general LLM inference")Find the cheapest OpenAI-compatible API for a specific task.
switch_from_openai(monthly_spend_usd: number = 100)Help user switch from OpenAI to cheaper alternative.
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
| Provider | $/1M tokens | vs Gonka |
|---|---|---|
| Gonka | $0.000325 | baseline |
| OpenAI | $2.50 | 7,681× more expensive |
| Anthropic | $3.00 | 9,230× more expensive |
| DeepSeek | $0.28 | 861× more expensive |
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")god_nodes()get_node(topic) or read_doc(doc_id)get_neighbors(node_id)shortest_path(concept_a, concept_b)Flow 3: Combined (technical validation before switching)
Live health grade: https://wmcp.sh/mcp/grade/mcp.gogonka.com (Current: B, 85/100)
Monitored by:
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 7,681× more.
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: 2.0.0 (Added knowledge graph tools)
Last Updated: June 22, 2026
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