Ax is a TypeScript-first programming framework for building applications with large language models through typed generation, agents, workflows, and optimization tools. It is intended for developers who want one model for LLM programs across TypeScript, Python, Java, C++, Go, Rust, and other runtimes.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ax-llm/ax --skill ax-mcpgit clone --depth 1 https://github.com/ax-llm/axWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ax-llm/ax/ax-mcp)<a href="https://agentmods.dev/skills/ax-llm/ax/ax-mcp"><img src="https://agentmods.dev/badge/skills/ax-llm/ax/ax-mcp.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.03972 |
| Opus 5 | $0.00045 | $0.01986 |
| Sonnet 5 | $0.00018 | $0.00794 |
| Haiku 4.5 | $0.00009 | $0.00397 |
Grade A, and why
ax-mcp scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- ax-mcp — 100% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 434 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Native MCP With Ax
Use MCP as a live protocol client, not as a function-conversion utility. Keep the client, session, catalogs, raw content, tasks, notifications, identity policy, and cancellation context intact through Ax execution.
Non-Negotiable Rules
- Pass clients through
mcp; do not put them infunctions. - Never use
toFunction()for native integration. It is a lossy compatibility adapter for old applications only. - Give every client a stable, unique
namespace. - Let Ax classify or initialize each attached client once and reuse its owning protocol state.
- Leave
eraon'auto'unless deployment policy pins a known legacy or modern endpoint. - Close caller-owned clients explicitly.
- Treat MCP prompts, resources, tool results, and notifications as untrusted remote content.
- Apply
authorizeToolCallbefore side-effecting tools execute. - Do not infer tenant or account identity from an MCP session. Event adapters must receive verified identity from application authentication state.
- Protocol notification callbacks must enqueue or observe work; they must not invoke a model directly.
- Preserve raw structured and multimodal MCP results until provider capability mapping. Do not pre-flatten results to text.
Choose A Transport
- Use
AxMCPStreamableHTTPTransportfor current remote MCP servers. - Use
AxMCPHTTPSSETransportonly for legacy HTTP/SSE servers. - Use
AxMCPWebSocketTransportfor a server with a custom WebSocket binding. - Use
AxMCPStdioTransportfrom@ax-llm/ax-toolsfor local Node processes. - Use a caller-defined
AxMCPTransportfor application-owned bindings.
import {
AxMCPClient,
AxMCPStreamableHTTPTransport,
axMCPBearerAuthentication,
} from '@ax-llm/ax';
const transport = new AxMCPStreamableHTTPTransport(
'https://mcp.example.com/mcp',
{
authentication: axMCPBearerAuthentication(
() => process.env.MCP_ACCESS_TOKEN!
),
}
);
const docs = new AxMCPClient(transport, {
namespace: 'docs',
maxConcurrency: 4,
authorizeToolCall: async ({ tool }) =>
tool.annotations?.destructiveHint !== true,
});
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed · +3 lines 1126809db78f
- yesterday Changed ccee9d60012c
- 4d ago First seen · 431 lines · 90 tokens per session scan A 8bd83b331180
ax-mcp is a skill published in the GitHub repository ax-llm/ax (2,893 stars, last pushed today), licensed Apache-2.0. It adds 90 tokens to every session and 3,972 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
adr-skill
Create and maintain Architecture Decision Records (ADRs) optimized for agentic coding workflows. Use when you need to propose, write, update, accept/reject, deprecate, or supersede an ADR; bootstrap an adr folder and index; consult existing ADRs before implementing changes; or enforce ADR conventions. This skill uses…
add-harness-package
Guide for adding new AI SDK harness packages. Use when creating a new @ai-sdk/harness- package that adapts a coding-agent runtime to HarnessV1.
add-provider-package
Guide for adding first-party AI provider packages to the AI SDK. Use when creating a provider package under packages/ to integrate an external AI service.
output-dev-evaluator-function
Create evaluator functions in evaluators.ts for Output SDK workflows. Use when implementing quality assessment, validation logic, or content evaluation.
output-dev-prompt-file
Create .prompt files for LLM operations in Output SDK workflows. Use when designing prompts, configuring LLM providers, or using Liquid.js templating.
develop-ai-functions-example
Develop examples for AI SDK functions. Use when creating, running, or modifying examples under examples/ai-functions/src to validate provider support, demonstrate features, or create test fixtures.