Open source · No lock-in · MCP, A2A, UTCP & Agent Skills

The full-stack platform for AI agents, agnostic by design

almyty sits on top of Claude, ChatGPT, Gemini, and the open-source models you self-host. Build one agent from several of them, give it your APIs as tools, and serve it over MCP, A2A, UTCP, and Agent Skills. Open source, no lock-in.

Self-host the source or use the hosted platform. No credit card to start.

app.almyty.com
An autonomous agent in almyty — the Customer Support Orchestrator detail view with its tools, integration endpoints, schedule, and audit log.

Connect over the protocol your client already speaks

MCPA2AUTCPSkillsOpenAPIGraphQLSOAPgRPC

Mixture of models and modes

Build one agent from several models

almyty sits on top of Claude, ChatGPT, Gemini, Mistral, and the open-source models you self-host. You do not pick one. You compose them: one model reasons, another refutes its answer, a self-hosted one handles the sensitive step. Or have several models work as a team — debate across rounds with a judge, run in parallel, or chain in sequence.

One agentmixture of models
Primary
ClaudeAnthropic

reasons and calls tools

Verifier
ChatGPTOpenAI

refutes the answer before it returns

Sensitive step
Mistralself-hosted

runs on your own infrastructure

…collaborating in modes like:SequentialParallelRaceDebate

Agnostic by design

No lock-in at any layer of the stack

Most agent tools marry you to one model vendor or one protocol. almyty keeps the choice yours, top to bottom.

Models

Every major LLM provider — OpenAI, Anthropic, Gemini, Bedrock, Vertex, Mistral, Groq, Ollama and more. Mix them per node.

APIs

OpenAPI, GraphQL, SOAP, Protobuf, and SDKs. Bring the services you already run, legacy included.

Memory

Pluggable agent memory and embeddings. Keep state where you want it, not where a vendor dictates.

Credentials

Your own credential vault and OAuth2 flows. almyty calls your APIs with your secrets, under your control.

Protocols

MCP, A2A, UTCP, and Agent Skills from one gateway. Clients connect the way they already work.

Deployment

Self-host with Docker and Kubernetes, or use the hosted platform. The same open-source core either way.

The pipeline

Schema in, agent out

A short path takes you from an API URL to an agent your clients can call. There is no glue code in between.

API

OpenAPI · GraphQL · SOAP

Tools

Typed & auto-generated

Gateway

MCP · A2A · UTCP · Skills

Agent

Multi-LLM pipeline

01

Connect an API

Import OpenAPI, GraphQL, SOAP, Protobuf, or an SDK. almyty parses the schema and reads every operation it defines.

02

Generate tools

Each operation becomes a typed, callable tool. When you need more, hand-write HTTP, JavaScript, GraphQL, or LLM tools.

03

Publish a gateway

Group tools behind one authenticated endpoint and expose them over MCP, A2A, UTCP, or Agent Skills at the same time.

04

Build an agent

Wire LLM calls, tool calls, conditions, and loops in the visual builder. Serve the result behind an OpenAI-compatible API.

What is in the platform

The whole toolchain, not just a wrapper

Schema parsing, tool generation, gateways, the agent runtime, and the operational pieces around them all live in one open codebase.

From OpenAPI to npm packages

OpenAPI and GraphQL, but also SOAP and Protobuf — the legacy services too. Or skip schemas and turn an npm package (stripe, aws-sdk) straight into tools.

Multi-model, with modes like debate

Autonomous agents that mix models and collaborate — debate across rounds, run in parallel, or verify each other before the answer returns — with memory and constraints across runs.

Every agent protocol

One gateway serves MCP, A2A, UTCP, and Agent Skills, with OAuth 2.1 for the clients that ask for it.

Any LLM provider

OpenAI, Anthropic, Gemini, Bedrock, Vertex, Mistral, Groq, Ollama, and more. A single pipeline can mix providers.

Reach any channel

Reach people on Slack, Discord, Telegram, WhatsApp, Teams, email, a web chat widget, or any inbound webhook.

Built to run in production

Multi-tenant orgs and RBAC, a credential vault, audit logging, rate-limit and PII-filter plugins, and a usage analytics suite.

For the CTO

Lower TCO, real governance, less risk

Before agents touch production, three questions decide it: what does it cost over time, who is allowed to do what, and how do we keep it from doing damage. almyty answers all three.

Lower TCO

  • Open-source core — self-host with no license fee
  • Bring your own keys, no token markup (or prepaid credits)
  • Agnostic at every layer — no vendor lock-in, take it with you
  • Flat per-seat pricing, predictable as you grow

Governance

  • Multi-tenant orgs with role-based access control
  • Audit log of sensitive actions
  • Human-in-the-loop approvals before irreversible steps
  • Credential vault — your secrets stay yours

Risk mitigation

  • Verify gates review output before it returns
  • Constraints stop agents repeating past mistakes
  • PII-filter and security-scanner plugins
  • Self-host or private cloud for data residency

Publish once

Connect from anything that speaks an agent protocol

The same tools are served across protocols at once, so a Claude Code session, an A2A peer, and a UTCP client all reach the gateway without you publishing it more than once.

MCPA2AUTCPSkills
connect.sh
# Add a gateway to any MCP client
claude mcp add petstore \
  --transport http https://api.almyty.com/acme/petstore

# Or call an agent over the OpenAI API
curl https://api.almyty.com/agents/$ID/v1/chat/completions \
  -H "Authorization: Bearer $ALMYTY_TOKEN" \
  -d '{"model":"agent","messages":[…]}'

For developers

Use it from the terminal, the browser, or your editor

A CLI suite that shares one login installs your tools into the AI coding agents your team already uses, runs agents on your own machine, and answers every agent on an OpenAI-compatible endpoint.

terminal
# one login, shared by every almyty CLI
$ npx @almyty/auth login

# drop a gateway's tools into your AI editor
$ npx @almyty/skills install acme/petstore

# talk to an agent right in the terminal
$ npx @almyty/chat research-bot

One CLI, one login

npx @almyty/cli covers auth, agents, chat, and skills, sharing a single credential store.

Skills for your editor

@almyty/skills install drops your tools into Claude Code, Cursor, Windsurf, and others.

Expose any environment

@almyty/runner runs anywhere (laptop, cloud VM, k8s pod, Docker) and makes that environment callable by your agents — run commands, use the local tools and CLIs it detects.

Questions

The short version

What does almyty actually do?+

It is the full-stack platform for AI agents: it turns any API schema into typed tools, serves those tools over MCP, A2A, UTCP, and Agent Skills, and runs the multi-LLM agents that use them. It stays agnostic at every layer, so your models, memory, credentials, and deployment target are your choice.

Which API formats can it import?+

OpenAPI, GraphQL, SOAP/WSDL, Protobuf, and language SDKs, each with a dedicated parser. Every operation in the schema becomes a callable tool.

What is the difference between a tool, a gateway, and an agent?+

A tool is a single callable operation. A gateway is a published endpoint that exposes a set of tools over a protocol such as MCP. An agent is a pipeline that calls LLMs and tools to do a job.

Do I have to use the visual agent builder?+

No. You can publish a gateway and call the tools from your own agents or from any MCP client. The builder is there when you want almyty to run the agent too.

Can I self-host it?+

Yes. The almyty core is open source and ships with Docker Compose and Kubernetes manifests. The hosted version at app.almyty.com runs the same core; governance and Enterprise features are commercially licensed, hosted or self-hosted.

How does almyty avoid lock-in?+

It stays agnostic at every layer. Models, API formats, memory backend, credential store, serving protocol, and deployment target are all your choice, and the platform is open source, so you can take it with you.

Which LLM providers are supported?+

Every major provider, including OpenAI, Anthropic, Gemini, Bedrock, Vertex, Mistral, Groq, and Ollama. A single pipeline can mix models from different providers.

Open source

Run the same platform we host

almyty is open source under Apache-2.0 — the core that runs app.almyty.com is the code you can read, fork, and self-host. One container to try it, Postgres and Redis alongside.

self-host
# one container — add Postgres and Redis
$ docker run -p 3000:3000 almyty/almyty

# or the full compose stack
$ docker compose -f docker-compose.allinone.yml up -d

Connect your first API

Import a schema, generate tools, and publish a gateway in a single sitting. Start on the hosted version or run the source yourself.