Blockchain RPC Nodes Optimized for AI Agents

Chainstack RPC endpoints use standard native APIs, making it straightforward for AI agents to call functions and get clear, well-documented responses for both successes and errors

Optimized for AI agents

Chainstack’s RPC nodes ensure reliable, spec-compliant blockchain nodes for your AI agents—providing standardized endpoints that your agent can easily integrate with.

MCP support

Chainstack supplies two different kinds of MCP servers—an RPC MCP server for the chains supported by Chainstack and the Developer Portal MCP server so that your agents can autonomously ingest the best practices and apply for on-chain operations

TLDR;

Plug-and-play native and spec-compliant RPC APIs.

Built-in health checks — both node native and platform health APIs.

Easy usage control — cap or uncap your requests usage in a click, works both for RPS & request volume.

Debug & Trace APIs — full API support for deep analysis and replication.

Transparent pricing — each standard request is 1 RU; each archive or Debug & Trace request is 2 RUs. That’s it.

Plug-and-play Easy to connect

Thanks to full adherence to each protocol’s native RPC specs (and comprehensive docs with examples), any LLM can connect to our nodes and interact with blockchain networks out-of-the-box. We truly mean any model—from the largest cloud AI to your local lightweight LM.

Any model

Compatible with any Large Language Model (LLM)—from cutting-edge giants (OpenAI GPT, Anthropic Claude, Google Gemini, DeepSeek) to compact local models at 1.5B or even less. If it’s an LLM, it works with Chainstack.

Chainstack AI Data availability

We constantly monitor the chains TVL & activity—we both have and constantly add all the chains that your AI Agents need to start extracting value right away.

Comprehensive chain support

We track blockchain activity and TVL closely—ensuring we support all the chains your AI agent might need, and continuously adding new ones. EVMs and non-EVMs alike.

Platform API

Our platform API is well-documented and lets your AI agents programmatically deploy new node endpoints for the networks they require on the fly.

Chainstack AI Subgraphs

We also have pre-deployed subgraphs for the popular networks and on-chain DeFi protocols like Uniswap, Curve, Pancake, QuickSwap, Lido, Aave and so on — on all the chains with the biggest TVL.

Built-in health checks

We expose all standard health check endpoints for easy use by your AI agents. For example, an agent can call node-specific APIs like `eth_syncing` on any supported protocol, or even check Chainstack’s overall platform status via our live status API. This gives your agent real-time awareness of node health and sync status.

Always up to date node clients

Your AI agents can query node software versions at any time (e.g. via the `web3_clientVersion` call), ensuring they’re always aware of the exact client and version they’re interacting with. This helps keep agents in sync with the underlying infrastructure. We handle all the updates and forks.

Chainstack AI Health check API

All the API health checks endpoints are available for easy AI Agent function calling: from the node native APIs like `eth_syncing` for each of the protocols to the overall platform status through our live dashboard.

Check the dashboard

Clear responses

All responses from our APIs are standardized and easy to parse—even error messages include helpful details and links to documentation. This consistency is especially useful when an agent hits a usage limit or needs to adjust its behavior (for example, if it must upgrade plans or reduce its requests per second). Your AI agent will know exactly what happened and what to do next.

Usage control

Monitor your agent’s RPC usage in real-time via our dashboard. You can set quotas to cap usage to your plan’s limits (to control costs) and get email alerts before each threshold is reached. This ensures your agent doesn’t unexpectedly run up usage without you knowing.

All the simulation your AI Agent needs is available out of the box.

With all the forking and call simulation, the AI Agents can increase the inference time as much as they need to make the best decision. They have all the tools.

eth_simulateV1

for EVMs

eth_call

for EVMs

simulateTransaction

for Solana

forking with Foundry and so on

Archive data and Debug & Trace APIs

Your AI agents can also leverage archive nodes and use Debug & Trace APIs. This means they have access to full historical chain data and low-level execution traces—enabling advanced analysis or extended reasoning on on-chain events when neededю

Ready for production

Once your AI agent is fine-tuned and generating value, you can switch to pay-as-you-go to lift any request quotas. Don’t hold your agent back with preset limits if it’s printing money.

Your AI Agent is fine-tuned and production ready?

You can enable the Pay-As-You-Go option and not limit the agent to a pre-allocated quota of requests. If the agent is printing money, you have the option to not stop the presses.

Full node request

1 RU

Archive node request

2 RUs

Debug&Trace API

2 RUs

Transparent pricing

Our usage is measured in Request Units (RUs) – for reference, a standard full-node call consumes 1 RU, while archive or Debug & Trace calls count as 2 RUs each. This simple metric makes it easy to predict costs as your agent scales.

Blockchain RPC Nodes Optimized for AI Agents

Chainstack RPC endpoints use standard native APIs, making it straightforward for AI agents to call functions and get clear, well-documented responses for both successes and errors

Optimized for AI agents

MCP support

Transparent pricing

Platform

Chains

Resources

Company

Support