python-utcp
Official python implementation of UTCP. UTCP is an open standard that lets AI agents call any API directly, without extra middleware.
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The Universal Tool Calling Protocol (UTCP) is a secure and scalable standard for defining and interacting with tools across various communication protocols. UTCP emphasizes scalability, extensibility, interoperability, and ease of use. It offers a modular core with a plugin-based architecture, making it extensible, testable, and easy to package. The repository contains the complete UTCP Python implementation with core components and protocol-specific plugins for HTTP, CLI, Model Context Protocol, file-based tools, and more.
README:
The Universal Tool Calling Protocol (UTCP) is a secure, scalable standard for defining and interacting with tools across a wide variety of communication protocols. UTCP 1.0.0 introduces a modular core with a plugin-based architecture, making it more extensible, testable, and easier to package.
In contrast to other protocols, UTCP places a strong emphasis on:
- Scalability: UTCP is designed to handle a large number of tools and providers without compromising performance.
- Extensibility: A pluggable architecture allows developers to easily add new communication protocols, tool storage mechanisms, and search strategies without modifying the core library.
- Interoperability: With a growing ecosystem of protocol plugins (including HTTP, SSE, CLI, and more), UTCP can integrate with almost any existing service or infrastructure.
- Ease of Use: The protocol is built on simple, well-defined Pydantic models, making it easy for developers to implement and use.
This repository contains the complete UTCP Python implementation:
-
core/- Coreutcppackage with foundational components (README) -
plugins/communication_protocols/- Protocol-specific plugins:
UTCP uses a modular architecture with a core library and protocol plugins:
The core/ directory contains the foundational components:
-
Data Models: Pydantic models for
Tool,CallTemplate,UtcpManual, andAuth -
Client Interface: Main
UtcpClientfor tool interaction - Plugin System: Extensible interfaces for protocols, repositories, and search
- Default Implementations: Built-in tool storage and search strategies
Install the core library and any required protocol plugins:
# Install core + HTTP plugin (most common)
pip install utcp utcp-http
# Install additional plugins as needed
pip install utcp-cli utcp-mcp utcp-textfrom utcp.utcp_client import UtcpClient
# Create client with HTTP API
client = await UtcpClient.create(config={
"manual_call_templates": [{
"name": "my_api",
"call_template_type": "http",
"url": "https://api.example.com/utcp"
}]
})
# Call a tool
result = await client.call_tool("my_api.get_data", {"id": "123"})UTCP supports multiple communication protocols through dedicated plugins:
| Plugin | Description | Status | Documentation |
|---|---|---|---|
utcp-http |
HTTP/REST APIs, SSE, streaming | ✅ Stable | HTTP Plugin README |
utcp-cli |
Command-line tools | ✅ Stable | CLI Plugin README |
utcp-mcp |
Model Context Protocol | ✅ Stable | MCP Plugin README |
utcp-text |
Local file-based tools | ✅ Stable | Text Plugin README |
utcp-socket |
TCP/UDP protocols | 🚧 In Progress | Socket Plugin README |
utcp-gql |
GraphQL APIs | 🚧 In Progress | GraphQL Plugin README |
For development, you can install the packages in editable mode from the cloned repository:
# Clone the repository
git clone https://github.com/universal-tool-calling-protocol/python-utcp.git
cd python-utcp
# Install the core package in editable mode with dev dependencies
pip install -e "core[dev]"
# Install a specific protocol plugin in editable mode
pip install -e plugins/communication_protocols/httpVersion 1.0.0 introduces several breaking changes. Follow these steps to migrate your project.
-
Update Dependencies: Install the new
utcpcore package and the specific protocol plugins you use (e.g.,utcp-http,utcp-cli). -
Configuration:
-
Configuration Object:
UtcpClientis initialized with aUtcpClientConfigobject, dict or a path to a JSON file containing the configuration. -
Manual Call Templates: The
providers_file_pathoption is removed. Instead of a file path, you now provide a list ofmanual_call_templatesdirectly within theUtcpClientConfig. -
Terminology: The term
providerhas been replaced withcall_template, andprovider_typeis nowcall_template_type. -
Streamable HTTP: The
call_template_typehttp_streamhas been renamed tostreamable_http.
-
Configuration Object:
-
Update Imports: Change your imports to reflect the new modular structure. For example,
from utcp.client.transport_interfaces.http_transport import HttpProviderbecomesfrom utcp_http.http_call_template import HttpCallTemplate. -
Tool Search: If you were using the default search, the new strategy is
TagAndDescriptionWordMatchStrategy. This is the new default and requires no changes unless you were implementing a custom strategy. -
Tool Naming: Tool names are now namespaced as
manual_name.tool_name. The client handles this automatically. -
Variable Substitution Namespacing: Variables that are substituted in different
call_templates, are first namespaced with the name of the manual with the_duplicated. So a key in a tool call template calledAPI_KEYfrom the manualmanual_1would be converted tomanual__1_API_KEY.
config.json (Optional)
You can define a comprehensive client configuration in a JSON file. All of these fields are optional.
{
"variables": {
"openlibrary_URL": "https://openlibrary.org/static/openapi.json"
},
"load_variables_from": [
{
"variable_loader_type": "dotenv",
"env_file_path": ".env"
}
],
"tool_repository": {
"tool_repository_type": "in_memory"
},
"tool_search_strategy": {
"tool_search_strategy_type": "tag_and_description_word_match"
},
"manual_call_templates": [
{
"name": "openlibrary",
"call_template_type": "http",
"http_method": "GET",
"url": "${URL}",
"content_type": "application/json"
},
],
"post_processing": [
{
"tool_post_processor_type": "filter_dict",
"only_include_keys": ["name", "key"],
"only_include_tools": ["openlibrary.read_search_authors_json_search_authors_json_get"]
}
]
}client.py
import asyncio
from utcp.utcp_client import UtcpClient
from utcp.data.utcp_client_config import UtcpClientConfig
async def main():
# The UtcpClient can be created with a config file path, a dict, or a UtcpClientConfig object.
# Option 1: Initialize from a config file path
# client_from_file = await UtcpClient.create(config="./config.json")
# Option 2: Initialize from a dictionary
client_from_dict = await UtcpClient.create(config={
"variables": {
"openlibrary_URL": "https://openlibrary.org/static/openapi.json"
},
"load_variables_from": [
{
"variable_loader_type": "dotenv",
"env_file_path": ".env"
}
],
"tool_repository": {
"tool_repository_type": "in_memory"
},
"tool_search_strategy": {
"tool_search_strategy_type": "tag_and_description_word_match"
},
"manual_call_templates": [
{
"name": "openlibrary",
"call_template_type": "http",
"http_method": "GET",
"url": "${URL}",
"content_type": "application/json"
}
],
"post_processing": [
{
"tool_post_processor_type": "filter_dict",
"only_include_keys": ["name", "key"],
"only_include_tools": ["openlibrary.read_search_authors_json_search_authors_json_get"]
}
]
})
# Option 3: Initialize with a full-featured UtcpClientConfig object
from utcp_http.http_call_template import HttpCallTemplate
from utcp.data.variable_loader import VariableLoaderSerializer
from utcp.interfaces.tool_post_processor import ToolPostProcessorConfigSerializer
config_obj = UtcpClientConfig(
variables={"openlibrary_URL": "https://openlibrary.org/static/openapi.json"},
load_variables_from=[
VariableLoaderSerializer().validate_dict({
"variable_loader_type": "dotenv", "env_file_path": ".env"
})
],
manual_call_templates=[
HttpCallTemplate(
name="openlibrary",
call_template_type="http",
http_method="GET",
url="${URL}",
content_type="application/json"
)
],
post_processing=[
ToolPostProcessorConfigSerializer().validate_dict({
"tool_post_processor_type": "filter_dict",
"only_include_keys": ["name", "key"],
"only_include_tools": ["openlibrary.read_search_authors_json_search_authors_json_get"]
})
]
)
client = await UtcpClient.create(config=config_obj)
# Call a tool. The name is namespaced: `manual_name.tool_name`
result = await client.call_tool(
tool_name="openlibrary.read_search_authors_json_search_authors_json_get",
tool_args={"q": "J. K. Rowling"}
)
print(result)
if __name__ == "__main__":
asyncio.run(main())A UTCPManual describes the tools you offer. The key change is replacing tool_provider with tool_call_template.
server.py
UTCP decorator version:
from fastapi import FastAPI
from utcp_http.http_call_template import HttpCallTemplate
from utcp.data.utcp_manual import UtcpManual
from utcp.python_specific_tooling.tool_decorator import utcp_tool
app = FastAPI()
# The discovery endpoint returns the tool manual
@app.get("/utcp")
def utcp_discovery():
return UtcpManual.create_from_decorators(manual_version="1.0.0")
# The actual tool endpoint
@utcp_tool(tool_call_template=HttpCallTemplate(
name="get_weather",
url=f"https://example.com/api/weather",
http_method="GET"
), tags=["weather"])
@app.get("/api/weather")
def get_weather(location: str):
return {"temperature": 22.5, "conditions": "Sunny"}No UTCP dependencies server version:
from fastapi import FastAPI
app = FastAPI()
# The discovery endpoint returns the tool manual
@app.get("/utcp")
def utcp_discovery():
return {
"manual_version": "1.0.0",
"utcp_version": "1.0.2",
"tools": [
{
"name": "get_weather",
"description": "Get current weather for a location",
"tags": ["weather"],
"inputs": {
"type": "object",
"properties": {
"location": {"type": "string"}
}
},
"outputs": {
"type": "object",
"properties": {
"temperature": {"type": "number"},
"conditions": {"type": "string"}
}
},
"tool_call_template": {
"call_template_type": "http",
"url": "https://example.com/api/weather",
"http_method": "GET"
}
}
]
}
# The actual tool endpoint
@app.get("/api/weather")
def get_weather(location: str):
return {"temperature": 22.5, "conditions": "Sunny"}You can find full examples in the examples repository.
The tool_provider object inside a Tool has been replaced by tool_call_template.
{
"manual_version": "string",
"utcp_version": "string",
"tools": [
{
"name": "string",
"description": "string",
"inputs": { ... },
"outputs": { ... },
"tags": ["string"],
"tool_call_template": {
"call_template_type": "http",
"url": "https://...",
"http_method": "GET"
}
}
]
}Configuration examples for each protocol. Remember to replace provider_type with call_template_type.
{
"name": "my_rest_api",
"call_template_type": "http", // Required
"url": "https://api.example.com/users/{user_id}", // Required
"http_method": "POST", // Required, default: "GET"
"content_type": "application/json", // Optional, default: "application/json"
"auth": { // Optional, authentication for the HTTP request (example using ApiKeyAuth for Bearer token)
"auth_type": "api_key",
"api_key": "Bearer $API_KEY", // Required
"var_name": "Authorization", // Optional, default: "X-Api-Key"
"location": "header" // Optional, default: "header"
},
"auth_tools": { // Optional, authentication for converted tools, if this call template points to an openapi spec that should be automatically converted to a utcp manual (applied only to endpoints requiring auth per OpenAPI spec)
"auth_type": "api_key",
"api_key": "Bearer $TOOL_API_KEY", // Required
"var_name": "Authorization", // Optional, default: "X-Api-Key"
"location": "header" // Optional, default: "header"
},
"headers": { // Optional
"X-Custom-Header": "value"
},
"body_field": "body", // Optional, default: "body"
"header_fields": ["user_id"] // Optional
}{
"name": "my_sse_stream",
"call_template_type": "sse", // Required
"url": "https://api.example.com/events", // Required
"event_type": "message", // Optional
"reconnect": true, // Optional, default: true
"retry_timeout": 30000, // Optional, default: 30000 (ms)
"auth": { // Optional, example using BasicAuth
"auth_type": "basic",
"username": "${USERNAME}", // Required
"password": "${PASSWORD}" // Required
},
"headers": { // Optional
"X-Client-ID": "12345"
},
"body_field": null, // Optional
"header_fields": [] // Optional
}Note the name change from http_stream to streamable_http.
{
"name": "streaming_data_source",
"call_template_type": "streamable_http", // Required
"url": "https://api.example.com/stream", // Required
"http_method": "POST", // Optional, default: "GET"
"content_type": "application/octet-stream", // Optional, default: "application/octet-stream"
"chunk_size": 4096, // Optional, default: 4096
"timeout": 60000, // Optional, default: 60000 (ms)
"auth": null, // Optional
"headers": {}, // Optional
"body_field": "data", // Optional
"header_fields": [] // Optional
}{
"name": "multi_step_cli_tool",
"call_template_type": "cli", // Required
"commands": [ // Required - sequential command execution
{
"command": "git clone UTCP_ARG_repo_url_UTCP_END temp_repo",
"append_to_final_output": false
},
{
"command": "cd temp_repo && find . -name '*.py' | wc -l"
// Last command output returned by default
}
],
"env_vars": { // Optional
"GIT_AUTHOR_NAME": "UTCP Bot",
"API_KEY": "${MY_API_KEY}"
},
"working_dir": "/tmp", // Optional
"auth": null // Optional (always null for CLI)
}CLI Protocol Features:
- Multi-command execution: Commands run sequentially in single subprocess
- Cross-platform: PowerShell on Windows, Bash on Unix/Linux/macOS
-
State preservation: Directory changes (
cd) persist between commands -
Argument placeholders:
UTCP_ARG_argname_UTCP_ENDformat -
Output referencing: Access previous outputs with
$CMD_0_OUTPUT,$CMD_1_OUTPUT - Flexible output control: Choose which command outputs to include in final result
{
"name": "my_text_manual",
"call_template_type": "text", // Required
"file_path": "./manuals/my_manual.json", // Required
"auth": null, // Optional (always null for Text)
"auth_tools": { // Optional, authentication for generated tools from OpenAPI specs
"auth_type": "api_key",
"api_key": "Bearer ${API_TOKEN}",
"var_name": "Authorization",
"location": "header"
}
}{
"name": "my_mcp_server",
"call_template_type": "mcp", // Required
"config": { // Required
"mcpServers": {
"server_name": {
"transport": "stdio",
"command": ["python", "-m", "my_mcp_server"]
}
}
},
"auth": { // Optional, example using OAuth2
"auth_type": "oauth2",
"token_url": "https://auth.example.com/token", // Required
"client_id": "${CLIENT_ID}", // Required
"client_secret": "${CLIENT_SECRET}", // Required
"scope": "read:tools" // Optional
}
}The testing structure has been updated to reflect the new core/plugin split.
To run all tests for the core library and all plugins:
# Ensure you have installed all dev dependencies
python -m pytestTo run tests for a specific package (e.g., the core library):
python -m pytest core/tests/To run tests for a specific plugin (e.g., HTTP):
python -m pytest plugins/communication_protocols/http/tests/ -vTo run tests with coverage:
python -m pytest --cov=utcp --cov-report=xmlThe build process now involves building each package (core and plugins) separately if needed, though they are published to PyPI independently.
- Create and activate a virtual environment.
- Install build dependencies:
pip install build. - Navigate to the package directory (e.g.,
cd core). - Run the build:
python -m build. - The distributable files (
.whland.tar.gz) will be in thedist/directory.
🚀 Transform any existing REST API into UTCP tools without server modifications!
UTCP's OpenAPI ingestion feature automatically converts OpenAPI 2.0/3.0 specifications into UTCP tools, enabling AI agents to interact with existing APIs directly - no wrapper servers, no API changes, no additional infrastructure required.
from utcp_http.openapi_converter import OpenApiConverter
import aiohttp
# Convert any OpenAPI spec to UTCP tools
async def convert_api():
async with aiohttp.ClientSession() as session:
async with session.get("https://api.github.com/openapi.json") as response:
openapi_spec = await response.json()
converter = OpenApiConverter(openapi_spec)
manual = converter.convert()
print(f"Generated {len(manual.tools)} tools from GitHub API!")
return manual
# Or use UTCP Client configuration for automatic detection
from utcp.utcp_client import UtcpClient
client = await UtcpClient.create(config={
"manual_call_templates": [{
"name": "github",
"call_template_type": "http",
"url": "https://api.github.com/openapi.json",
"auth_tools": { # Authentication for generated tools requiring auth
"auth_type": "api_key",
"api_key": "Bearer ${GITHUB_TOKEN}",
"var_name": "Authorization",
"location": "header"
}
}]
})- ✅ Zero Infrastructure: No servers to deploy or maintain
- ✅ Direct API Calls: Native performance, no proxy overhead
- ✅ Automatic Conversion: OpenAPI schemas → UTCP tools
- ✅ Selective Authentication: Only protected endpoints get auth, public endpoints remain accessible
- ✅ Authentication Preserved: API keys, OAuth2, Basic auth supported
- ✅ Multi-format Support: JSON, YAML, OpenAPI 2.0/3.0
- ✅ Batch Processing: Convert multiple APIs simultaneously
-
Direct Converter:
OpenApiConverterclass for full control - Remote URLs: Fetch and convert specs from any URL
- Client Configuration: Include specs directly in UTCP config
- Batch Processing: Process multiple specs programmatically
- File-based: Convert local JSON/YAML specifications
📖 Complete OpenAPI Ingestion Guide - Detailed examples and advanced usage
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API Improvement Proposals (AIPs) are design documents that provide high-level, concise documentation for API development at Google. The goal of AIPs is to serve as the source of truth for API-related documentation and to facilitate discussion and consensus among API teams. AIPs are similar to Python's enhancement proposals (PEPs) and are organized into different areas within Google to accommodate historical differences in customs, styles, and guidance.
kong
Kong, or Kong API Gateway, is a cloud-native, platform-agnostic, scalable API Gateway distinguished for its high performance and extensibility via plugins. It also provides advanced AI capabilities with multi-LLM support. By providing functionality for proxying, routing, load balancing, health checking, authentication (and more), Kong serves as the central layer for orchestrating microservices or conventional API traffic with ease. Kong runs natively on Kubernetes thanks to its official Kubernetes Ingress Controller.
speakeasy
Speakeasy is a tool that helps developers create production-quality SDKs, Terraform providers, documentation, and more from OpenAPI specifications. It supports a wide range of languages, including Go, Python, TypeScript, Java, and C#, and provides features such as automatic maintenance, type safety, and fault tolerance. Speakeasy also integrates with popular package managers like npm, PyPI, Maven, and Terraform Registry for easy distribution.
apicat
ApiCat is an API documentation management tool that is fully compatible with the OpenAPI specification. With ApiCat, you can freely and efficiently manage your APIs. It integrates the capabilities of LLM, which not only helps you automatically generate API documentation and data models but also creates corresponding test cases based on the API content. Using ApiCat, you can quickly accomplish anything outside of coding, allowing you to focus your energy on the code itself.
aiohttp-pydantic
Aiohttp pydantic is an aiohttp view to easily parse and validate requests. You define using function annotations what your methods for handling HTTP verbs expect, and Aiohttp pydantic parses the HTTP request for you, validates the data, and injects the parameters you want. It provides features like query string, request body, URL path, and HTTP headers validation, as well as Open API Specification generation.
ain
Ain is a terminal HTTP API client designed for scripting input and processing output via pipes. It allows flexible organization of APIs using files and folders, supports shell-scripts and executables for common tasks, handles url-encoding, and enables sharing the resulting curl, wget, or httpie command-line. Users can put things that change in environment variables or .env-files, and pipe the API output for further processing. Ain targets users who work with many APIs using a simple file format and uses curl, wget, or httpie to make the actual calls.
OllamaKit
OllamaKit is a Swift library designed to simplify interactions with the Ollama API. It handles network communication and data processing, offering an efficient interface for Swift applications to communicate with the Ollama API. The library is optimized for use within Ollamac, a macOS app for interacting with Ollama models.
ollama4j
Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It facilitates communication with the Ollama server and provides models for deployment. The tool requires Java 11 or higher and can be installed locally or via Docker. Users can integrate Ollama4j into Maven projects by adding the specified dependency. The tool offers API specifications and supports various development tasks such as building, running unit tests, and integration tests. Releases are automated through GitHub Actions CI workflow. Areas of improvement include adhering to Java naming conventions, updating deprecated code, implementing logging, using lombok, and enhancing request body creation. Contributions to the project are encouraged, whether reporting bugs, suggesting enhancements, or contributing code.