Agent Framework for TypeScript MCP server
Commit Nov 9, 2026Provides a TypeScript implementation of the Microsoft Agent Framework programming model for building interoperable AI agents.
Also known as polymind-inc/agent-framework-js
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What is Agent Framework for TypeScript MCP?
Agent Framework for TypeScript provides a TypeScript implementation of the Microsoft Agent Framework programming model for building interoperable AI agents.
Summary generated from the project's README
About Agent Framework for TypeScript MCP server
Building interoperable AI agents using TypeScript is possible with this implementation of the Microsoft Agent Framework programming model. It provides developers with a way to create agents that maintain semantic parity with official .NET, Python, and Go versions. By using the same names, wire formats, and observable behaviors, this framework ensures that agents can communicate across different language environments without losing data or changing logic.
Developers can integrate this library into Node.js, Deno, Bun, or browser environments. It offers specialized subpaths for different needs, such as the OpenAI and Anthropic chat clients, or the Model Context Protocol client for using MCP server tools. The core package includes essential components like Agent, AgentSession, and the tool function. Because it uses standard web patterns like AbortSignal for cancellation and koa-style middleware, it fits naturally into existing JavaScript ecosystems.
What you can do with it
- 1Create interoperable AI agentsA developer can build a TypeScript agent that uses the same wire format and concepts as Python or .NET implementations.
- 2Integrate MCP server toolsYou can use this framework to bring tools from an MCP server directly into your agent's toolset.
- 3Implement streaming and awaited responsesAn AI client can handle agent responses as either a single awaited result or an asynchronous stream of updates.
Written from the project's README. Every use case is checked against a quote from it.
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README
View on GitHubAgent Framework for TypeScript
A TypeScript implementation of the Microsoft Agent Framework programming model, designed for semantic parity with the official .NET and Python and Go implementations.
This is an independent community implementation. It is not an official Microsoft product, and it is not affiliated with, endorsed by, or reviewed by Microsoft. See Trademarks.
The Agent Framework has first-party implementations for .NET, Python and Go. There is no
TypeScript one. This project fills that gap on the framework's own terms rather than inventing a
parallel programming model: the same concepts, the same names, the same wire format, and the same
observable behaviour — expressed in TypeScript idioms. The explicit goal is for this code to be in
a shape that could be adopted upstream, the way microsoft/agent-framework-go
sits alongside the .NET and Python implementations in microsoft/agent-framework.
Everything from the repository name to the package layout to the naming generation to the release
cadence is chosen with that in mind.
Contents
- Quickstart
- Packages
- Parity with the reference implementations
- Where the TypeScript API differs in shape
- Design principles
- Coverage
- Requirements
- Examples
- Known limitations
- Stability and versioning
- Contributing
Quickstart
npm install @polymind-inc/agent-framework zod
import { Agent, tool } from '@polymind-inc/agent-framework';
import { OpenAIChatClient } from '@polymind-inc/agent-framework/openai';
import { z } from 'zod';
const weather = tool({
name: 'get_weather',
description: 'Get the current weather for a location',
parameters: z.object({ location: z.string() }),
execute: async ({ location }) => `${location} is sunny, 25°C`,
});
const agent = new Agent({
client: new OpenAIChatClient({ model: 'gpt-4o-mini' }),
instructions: 'You are a helpful weather assistant.',
tools: [weather],
});
const session = agent.createSession();
// Streaming.
for await (const update of agent.run('What is the weather in Tokyo?', { session })) {
process.stdout.write(update.text);
}
// Awaited — the same call, folded into a single response.
const res = await agent.run('And in Osaka?', { session });
console.log(res.text);
agent.run() returns one hybrid value that is both a PromiseLike<AgentResponse> and an
AsyncIterable<AgentResponseUpdate>. There is no second streaming method to learn, and the
non-streaming result is a fold of the stream rather than a separate code path — the same principle
the Go implementation uses.
Packages
One package to install: @polymind-inc/agent-framework. The root entry is the agent core;
every other capability lives under a subpath. The subpaths are plain static re-exports, so a
bundler tree-shakes whatever you do not import.
| Import | Provides |
|---|---|
@polymind-inc/agent-framework |
Agent, AgentSession, the Message/Content model, tool(), middleware, and the ChatClient seam |
@polymind-inc/agent-framework/node |
Node-only adapters, including directorySkillsSource and file-backed history |
@polymind-inc/agent-framework/openai |
OpenAI and Azure OpenAI chat client (Responses API) |
@polymind-inc/agent-framework/anthropic |
Anthropic chat client (Messages API) |
@polymind-inc/agent-framework/mcp |
Model Context Protocol client integration — MCP server tools as framework tools |
@polymind-inc/agent-framework/a2a |
Agent2Agent (A2A) protocol client — a remote A2A agent used as an agent |
@polymind-inc/agent-framework/foundry |
Microsoft Foundry chat client, with the Hosted Agent adapter under /foundry/hosting |
@polymind-inc/agent-framework/agentserver |
Foundry container protocol servers (Responses v2.0.0 and Invocations), with /agentserver/node and /agentserver/observability companions |
@polymind-inc/agent-framework/testing |
MockChatClient and friends for testing agents without a live provider |
Under the hood the framework is developed and published as a family of
@polymind-inc/agent-framework-* constituent packages, released in lockstep and pinned to exact
versions by the main package. They exist to keep the codebase modular and the upstream story
flexible; importing them directly works — every subpath above is a static re-export of one of
them — but the supported, documented surface is @polymind-inc/agent-framework. The names mirror
the Python distribution layout (agent-framework, agent-framework-core, agent-framework-openai,
…) so that a move to a first-party scope is a mechanical rename.
Parity with the reference implementations
Parity here means semantic parity, not signature parity. The rule this project follows is the one the Go implementation states for itself:
Respect language idioms — signatures follow the host language; semantics (default values, side effects, event emission, checkpointing, tool invocation, serialization) match the other implementations exactly. A differently shaped API is not, by itself, a parity violation.
Concretely, that commitment has three parts.
Naming follows the current (v1.13) generation. Pre-rename names from older articles
(ChatAgent, AgentThread, AgentRunResponse, ChatMessage) are not used.
| Concept | TypeScript | .NET | Python | Go |
|---|---|---|---|---|
| Agent | Agent |
AIAgent / ChatClientAgent |
Agent |
agent.Agent |
| Conversation | AgentSession |
AgentSession |
AgentSession |
agent.Session |
| Message | Message |
ChatMessage |
Message |
message.Message |
| Content | Content (discriminated union) |
AIContent hierarchy |
Content (single class) |
message.Content |
| Response | AgentResponse / AgentResponseUpdate |
same | same | agent.Response / ResponseUpdate |
| Chat client | ChatClient |
IChatClient |
SupportsChatGetResponse |
ProviderConfig.Run |
| Tool | Tool / FunctionTool / tool() |
AITool / AIFunction |
FunctionTool / @tool |
tool.Tool / functool |
| History | HistoryProvider |
ChatHistoryProvider |
HistoryProvider |
agent.HistoryProvider |
| Context | ContextProvider |
AIContextProvider |
ContextProvider |
agent.ContextProvider |
The wire format is interoperable. Serialized messages, content, sessions and checkpoints use
camelCase properties and the same type discriminator literals as the Python implementation.
Unknown content is preserved and round-tripped rather than dropped, so a payload produced by
another implementation survives a trip through this one unchanged.
Behaviour is verified against the reference source, not inferred. Where the implementations disagree, the order of authority is .NET, then Python, then Go. Defaults, folding rules, the function-calling loop, the approval flow and cancellation semantics were each read out of the reference code rather than guessed at.
Where the TypeScript API differs in shape
Deliberate divergences, and the reason for each:
| Topic | Reference implementations | This implementation | Why |
|---|---|---|---|
| Streaming | .NET splits RunAsync / RunStreamingAsync; Python uses stream= |
one run() returning a thenable and async-iterable |
Awaiting or iterating is the natural JS distinction |
| Content model | class hierarchy (.NET), single class + type (Python) |
discriminated union | Exhaustiveness checking is TypeScript's strongest guarantee |
| Tool schemas | reflection (.NET), Pydantic (Python) | Standard Schema v1 or raw JSON Schema | JS erases types at runtime, so schemas have to be values |
| Middleware | decorators + builder (.NET), mixin layers (Python) | koa-style (ctx, next) functions |
The established composition idiom in the JS ecosystem |
| Cancellation | CancellationToken, context.Context |
AbortSignal |
The web platform standard |
| Dependency injection | Microsoft.Extensions.DependencyInjection (.NET) |
none — explicit constructor injection | Matches the Python and Go decision |
Design principles
- TypeScript-first, ESM only. Types are part of the API. Discriminated unions, generics and overloads are used so that code which typechecks, works. There is no CommonJS build.
- A runtime-agnostic core. The core runs on Node.js, Deno, Bun, edge runtimes and in browsers. Node-specific concerns live in other packages.
- Wire compatibility. Serialization is interoperable with the other implementations, including preservation of content this implementation does not understand.
- Minimal dependencies. The core's only runtime dependency is
@opentelemetry/api— the API package alone, which is a no-op until an SDK is configured. Schema libraries are accepted through the Standard Schema interface, never depended on. - Non-streaming is a fold of streaming. There is one execution path, not two.
- Security is documented at the API. Prompt injection, the trust boundary around session restoration, and unapproved tool execution each carry an explicit "Security considerations" note in the TSDoc.
Coverage
| Area | Status |
|---|---|
| Agent, sessions, tools, middleware, streaming | Implemented |
| Function-calling loop, tool approval, continuation tokens | Implemented |
| OpenAI / Azure OpenAI, Anthropic and Microsoft Foundry providers | Implemented |
| Microsoft Foundry Hosted Agent hosting (Responses and Invocations protocols) | Implemented |
ContextProvider / HistoryProvider |
Implemented |
| OpenTelemetry GenAI instrumentation | Implemented |
| MCP client (tools) | Implemented |
| Agent Skills (progressive disclosure), including skills served over MCP and by a Foundry toolbox | Implemented |
| A2A client | Implemented |
| Workflows (graph/superstep engine, checkpointing, orchestrations) | Designed, not implemented — the next milestone |
| History compaction | Planned |
| Generic hosting (A2A / AG-UI / OpenAI-compatible surfaces) | Planned |
| DevUI, declarative YAML agents, durable execution, evaluation | Out of scope by design (code-first, as in the Go implementation) |
Requirements
- Node.js >= 24 (active LTS). ESM only — there is no CommonJS build.
- TypeScript: type resolution is verified with TypeScript 7 under
moduleResolution: bundlerandnodenext. Declarations are emitted withisolatedDeclarations.
Examples
Runnable examples live in examples/: getting started, multimodal input, agent
delegation, Foundry chat and hosting, middleware, context providers, Anthropic, OpenAI hosted
tools, MCP, and A2A. See examples/README.md for the commands and the
environment variables each one needs.
Known limitations
- Workflows are not implemented yet — the graph/superstep engine, checkpointing and the high-level orchestrations are the next milestone.
OpenAIChatClientsupports the Responses API only.api: 'chat_completions'is permanently out of scope; point a Chat Completions-only provider at a Responses-compatible endpoint, or implement theChatClientinterface directly.- The MCP integration covers tools, and resources for skill discovery — no sampling, elicitation or prompts.
- Agent Skills are served from code, from a
SKILL.mddocument you supply, over MCP, or from a local directory through the Node-onlydirectorySkillsSource. MCParchiveskills, resource templates and directskill://references are not implemented. - The A2A package is a client. Serving a framework agent over A2A, push notifications, task
listing and cancellation are not covered; use
@a2a-js/sdkdirectly for those. - A hosted container persists responses in the Foundry storage service by default (matching the reference implementations); the background replay log lives beside the sandbox state, so stream replay after a sandbox recycle fails closed rather than resuming.
- The core runs in browsers, but calling a model provider directly from a browser exposes your API key — run agents server-side.
- Because
agent.run()returns a hybrid thenable, type-aware lint rules such as@typescript-eslint/no-floating-promiseswill flag a deliberately unconsumed call. Consume the stream orvoidit explicitly. - Session envelope interoperability with the .NET and Python implementations is not finalized — their envelopes currently differ from each other.
Stability and versioning
The public API is stable but not frozen: surface changes are made deliberately, motivated by
alignment with the reference implementations. During 0.x, minor releases may contain breaking
changes; patch releases are fixes only. All packages are versioned and released in
lockstep, so a single CHANGELOG.md entry covers the set. Releases are published
from CI with npm provenance.
Contributing
Contributions are welcome — see CONTRIBUTING.md. Parity bugs, where this implementation behaves differently from .NET, Python or Go, are the highest-priority class of issue. Because the goal is upstream contribution, changes are held to the naming, wire-format and semantic rules described above; the contributing guide spells them out.
Security issues should be reported privately — see SECURITY.md.
Trademarks
"Microsoft", "Microsoft Agent Framework" and "Microsoft Foundry" are trademarks of Microsoft Corporation. They are used here descriptively, to identify the programming model and the services this project implements and interoperates with. This project is not affiliated with or endorsed by Microsoft.
License
Agent Framework for TypeScript MCP questions
Is this an official Microsoft product?
No, this is an independent community implementation and is not affiliated with or endorsed by Microsoft.
Does it support streaming responses?
Yes, the run() method returns a value that can be used as both a Promise and an AsyncIterable for streaming updates.
Can I use MCP tools with this framework?
Yes, there is a specific package for Model Context Protocol client integration that allows MCP server tools to be used as framework tools.
What environments can this run in?
The core is runtime-agnostic and can run on Node.js, Deno, Bun, edge runtimes, and in browsers.