GMGN OpenAPI now has three plans — Free, Plus, Pro. Your plan sets how much weight your key can spend each second, and Pro carries 10x what Free does. If you've been pacing your loop around the rate limit instead of around the market, that's the constraint this moves.

🎉 GMGN OpenAPI Rate Limit Update — Throughput Doubled! 🚀 Effective immediately (2026-05-13), we've upgraded the limits across ALL modules. Leaky-bucket just got a major boost: From rate=10/capacity=10 → rate=20/capacity=20 That means you can now fire twice as many requests per second as before! New sustained throughput: W = weight | RPS = sustained requests per second Formula: RPS = 20 ÷ W Developers, go build faster, query harder, and scale smoother than ever. The GMGN API is cooking — enjoy the extra power! 🔥 Create Your Free API Key NOW (Multi-Chain Supported): 👉🏻 Need Help? Join TG chat group: 👉🏻 #Hermes# #Openclaw# #Agent# #TradingBots# #Trenches# #AItrading#

# Practical and Useful Patterns with ADK 📜 Got an OpenAPI/Swagger spec? That's all you need to turn APIs into tools — ADK's OpenAPI Tools integrate existing REST APIs into agents with minimal effort. 📌 Title: OpenAPI Tools — Auto-Generating Tools from OpenAPI Specs 🔗 URL: 🧩 Overview ADK's OpenAPIToolset auto-generates RestApiTool instances from OpenAPI (Swagger) specifications. Each endpoint becomes an agent tool with automatic input validation. Set `auth_scheme` and `auth_credential` once, and authentication is automatically applied to all generated tools — no per-tool auth code needed. 🛠 Usage Auto-generating tools from an OpenAPI spec. Import `OpenAPIToolset` from ` and `APIKeyAuth` from `google.adk.auth`. Create the toolset with `OpenAPIToolset(spec_url="", auth_scheme=APIKeyAuth(header_name="X-API-Key"), auth_credential="your-api-key-here")`, which auto-generates tools from the spec with authentication automatically applied to all endpoints. Pass the `toolset` to an `Agent`'s `tools` list to make every API endpoint available as an agent tool. Using a local OpenAPI spec file: For local OpenAPI spec files, load the YAML with ` and pass it as `OpenAPIToolset(spec_dict=spec, base_url="")`, using the `spec_dict` parameter for the parsed dictionary and `base_url` to specify the API's base URL. 🏗 Practical Patterns **Instant Integration of Existing APIs**: If your internal microservices publish OpenAPI specs, they become agent tools without writing code. The spec's `description` fields serve as tool descriptions, so spec quality directly impacts agent accuracy. To integrate multiple APIs, create separate `OpenAPIToolset` instances for each service -- for example, a user service with `OpenAPIToolset(spec_url="https://user-service.internal/openapi.json", auth_scheme=APIKeyAuth(header_name="Authorization"), auth_credential="Bearer token123")` and an order service with its own spec URL and credentials. Pass both to the `Agent` as `tools=[user_api, order_api]`, allowing per-service access control with different authentication configurations. **Input Validation**: Automatic validation based on OpenAPI schema definitions (required, type, enum, etc.) prevents invalid API calls. **Incremental Integration**: Start by tooling only read-only GET endpoints. Verify behavior, then gradually add POST/PUT/DELETE endpoints. 💡 Use Cases 🏢 Agent integration of internal microservices 🛒 E-commerce API tooling (product search, order management) 📊 Natural language queries via data analysis API integration 🔗 Third-party SaaS API integration ⚠️ Caveats - Insufficient `description` fields in OpenAPI specs prevent the LLM from selecting the right tool. Review spec quality beforehand. - Never hardcode `auth_credential`. Retrieve from environment variables or Secret Manager. - Too many endpoints make LLM tool selection inaccurate. Configure the Toolset with only the endpoints you need. ✨ With OpenAPI Tools, your API specs become agent capabilities directly. Make the most of your existing API documentation! #ADK# #AIAgent#

Hey agent, can we make our OpenAPI spec be agent discoverable? Like, return the right API specs when the agent writes a summary of the task? Five minutes later the agent wires up an embedding model on Cloudflare. I'm kinda impressed by both Cloudflare and the agent capabilities here really.

A wallet's win rate is its highlight reel — it skips the slippage. GMGN OpenAPI scores the wallet, then backtests the copy under real latency, slippage, and gas. Ask it: "Score wallet [address] for copy-trading on Robinhood."

Checking multiple tokens means multiple tabs, one at a time. GMGN OpenAPI does it in one batch — basics, security, and holder distribution, every token at once. "Batch-check the basics, security, and holder distribution for [address1, address2, address3] ."

You wrote the strategy. Staying awake to run it isn't part of it. GMGN OpenAPI runs it instead — open-source demo, no code. Doesn't blink, get bored, or fat-finger the size.

Stop managing workflows manually. Start automating them. With @ClawUpAI 's Public API, you can programmatically manage agents, teams, and chats, while OpenAPI support makes SDK generation simple across your preferred language. Build faster. Automate more. Scale effortlessly.See how it works 👇

Build automations, not manual workflows. With @ClawUpAI 's Public API, you can programmatically manage agents, teams, and chats. OpenAPI support makes it easy to generate SDKs in your preferred programming language. See how it works 👇

Screening a new token is the same filters every time — enough KOLs in, holders spread out, bundled supply low. GMGN OpenAPI takes that as one sentence, and your agent runs the screen. "Screen new BSC tokens: 2+ KOL buys, top 10 holders under 20%, bundled supply under 20%." 50+ free, open-source skills —