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Donkey Development Kit (DDK)

donkey-kit on PyPI

Donkey Development Kit

An SDK for consuming Agent Fabric capabilities — governed model and tool access — from your own agent framework, in your own IDE, without adopting Mule.

Project status — alpha. This is an early release (Development Status :: 3 - Alpha). The LLM data plane is live-verified; most other surfaces are verification-gated (see What's verified below). Install it from PyPI with pip install donkey-kit — see Install. Unofficial: an independent project, not affiliated with or endorsed by Salesforce or MuleSoft.

Already integrated the pre-rebrand SDK? The move to Donkey Development Kit is a clean break — no import shims, env fallbacks, or OpenTelemetry dual-emit. The migration guide maps every renamed import, class, CLI, config key, and environment variable, and calls out the breaking OpenTelemetry attribute-namespace change.

Support & trademark statement (please read)

"Agent Fabric" is a MuleSoft (Salesforce) product name, not a generic term. MuleSoft, Anypoint, Omni Gateway, and Agent Fabric are Salesforce trademarks.

Maintainer & support. This is an independent, community-maintained project, published under the org-scoped Donkey-Development-Kit name — it is not affiliated with, endorsed by, or supported by Salesforce or MuleSoft. It is provided as-is, without warranty of any kind; the maintainers triage issues and pull requests on a best-effort basis, with no SLA. Because it ships under a distinct, org-scoped name, only the descriptive form ("an SDK for MuleSoft Agent Fabric") appears in prose — the package does not represent itself as a first-party, official-status SDK.

Licensed under Apache-2.0. See docs/unsupported-boundary.md for exactly which platform APIs this SDK calls and their support classification.

Documentation

Two audiences, two doc sets:

  • Use the SDK → the documentation site: https://docs.donkey-kit.dev/. Install and configure, per-framework model access, the governed error taxonomy, and what to trust today — everything you need to point your agent at a governed proxy.
  • See it run → runnable demos live in the companion repo donkey-development-kit-demos: the framework-free client, native framework objects, the governed error taxonomy, and the screen-recording scripts.
  • Understand or contribute to the repo:
    • ARCHITECTURE.md — how the SDK is built: the layered stack, the framework-free core, verification discipline, the error taxonomy, and framework tiering.
    • CONTRIBUTING.md — how to work in the repo: the branch/PR/release workflow, the testing strategy, coding conventions, and the docs-sync rule.
    • docs/verified-apis.md — the verification ledger: the single source of truth for what is confirmed against a real sandbox and what is still blocked.

Install

pip install "donkey-kit[llm,langgraph]"   # base + raw client + one framework

To work on the SDK itself, install from source instead:

git clone https://github.com/Donkey-Development-Kit/donkey-development-kit.git
cd donkey-development-kit/python
pip install -e ".[llm,langgraph]"

Extras are one per framework (langgraph, adk, strands, agent_framework, openai-agents, anthropic, crewai, llamaindex) plus mcp, a2a, otel, cli, local, test (the conformance pytest plugin — pytest --donkey-conformance --agent=my_app.agent:build), and all. all is everything that installs together — llm, langgraph, mcp, otel, cli, local, test — and leaves out the seven other framework extras, whose current upstream releases cannot all be installed together. Add the one framework you use: donkey-kit[all,crewai]. Configuration and first-agent walkthroughs live on the documentation site.

Framework support

The roster is deliberately one deep, seven shallow (BG §1.8): one adapter held to the full conformance bar, the rest supported through the three-line connection_kwargs() escape hatch. Every framework below returns its framework's own native object — never a wrapper.

Tier Frameworks What it means
Conformance-tested The raw client (donkey.llm.client()) and LangGraph Held to the conformance suite in CI — the governed contract is proven end to end.
Supported via connection_kwargs() Google ADK, Strands, Microsoft Agent Framework, OpenAI Agents SDK, Anthropic SDK, CrewAI, LlamaIndex Governed kwargs verified at the connection_kwargs() level, not conformance-tested.

connection_kwargs() works for all eight; a second deep adapter is promoted from demand evidence, one at a time (#223/#244) — never guessed up front. See the framework pages for each.

What's verified (verification discipline)

The LLM data plane — governed model access through the Omni Gateway proxy — is live-verified against a real Anypoint sandbox, and both the framework-free client and the framework adapters are wired to that verified contract — LangGraph is held to the conformance suite, the other seven are supported at the connection_kwargs() level (see Framework support). Everything still gated raises NotImplementedError("blocked on verification: …") rather than guessing at an unverified endpoint, header, or class name — that currently includes Exchange→MCP tool discovery, the provisioning control-plane, and the exact framework adapter class names/kwargs.

The discipline behind this is documented in ARCHITECTURE.md → Verification discipline; the row-by-row worklist is docs/verified-apis.md.

Conformance exemptions

The conformance plugin holds the SDK to the same bar it asks of your agent. Where a framework legitimately cannot satisfy a scenario, the reason is asserted in code (KNOWN_LIMITATIONS) and published here as credibility — never a silent skip (the conformance kit):

Framework Scenario Why it's exempt
ADK model(), CrewAI correlation ID propagated The framework owns the transport — LiteLLM for ADK's model(), CrewAI's native OpenAI provider for CrewAI — so the SDK's httpx client cannot be injected and the correlation ID ends up per-client, not per-run. For ADK, a LiteLLM logger callback may recover trace correlation later. ADK's gemini() (Format=Gemini proxy) injects the shared client and records no exemption (#691).
LlamaIndex, Microsoft Agent Framework correlation ID propagated These adapters receive a static default_headers snapshot, which deliberately excludes the per-run correlation ID. Without the SDK's httpx client, donkey.run(id=...) cannot update their request headers.
ADK model(), CrewAI gateway identity observed The framework owns the transport (LiteLLM for ADK's model(), CrewAI's native OpenAI provider for CrewAI), so no response reaches the SDK's _on_response hook. When every resolved adapter is non-observing, donkey.last_call reports UNAVAILABLE and names them in surface.
LlamaIndex, Microsoft Agent Framework gateway identity observed These adapters receive default_headers, not the SDK's httpx client, so no response reaches _on_response. When every resolved adapter is non-observing, donkey.last_call reports UNAVAILABLE and names them in surface.
CrewAI JWT refreshed per send CrewAI's native OpenAI provider owns the transport and builds its own clients, so the rotating JWT the SDK adds per send never reaches its requests. donkey.crewai.llm() and connection_kwargs() raise ConfigError in jwt mode; use client-id auth with CrewAI. ADK's model() and gemini(), LlamaIndex and Microsoft Agent Framework send through the SDK's client and carry the rotating JWT on async calls (jwt mode).
CrewAI budget refusal not retried CrewAI wraps every LLM call in its own rate-limit retry (3 attempts) and treats any 429 as a rate limit, so a TokenBudgetExceeded refusal is sent 3 times. CrewAI has no setting to turn it off; the OpenAI client underneath has max_retries=0. Every other adapter sends a budget refusal once (#734).

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