| Name | mcp-server-llmling JSON |
| Version |
0.6.0
JSON |
| download |
| home_page | None |
| Summary | MCP (Model context protocol) server with LLMling backend |
| upload_time | 2025-10-06 20:30:00 |
| maintainer | None |
| docs_url | None |
| author | Philipp Temminghoff |
| requires_python | >=3.13 |
| license | MIT License
Copyright (c) 2024, Philipp Temminghoff
Permission is hereby granted, free of charge, to any person obtaining a copy
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The above copyright notice and this permission notice shall be included in all
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# mcp-server-llmling
[](https://pypi.org/project/mcp-server-llmling/)
[](https://pypi.org/project/mcp-server-llmling/)
[](https://pypi.org/project/mcp-server-llmling/)
[](https://pypi.org/project/mcp-server-llmling/)
[](https://pypi.org/project/mcp-server-llmling/)
[](https://pypi.org/project/mcp-server-llmling/)
[](https://pypi.org/project/mcp-server-llmling/)
[](https://github.com/phil65/mcp-server-llmling/releases)
[](https://github.com/phil65/mcp-server-llmling/graphs/contributors)
[](https://github.com/phil65/mcp-server-llmling/discussions)
[](https://github.com/phil65/mcp-server-llmling/forks)
[](https://github.com/phil65/mcp-server-llmling/issues)
[](https://github.com/phil65/mcp-server-llmling/pulls)
[](https://github.com/phil65/mcp-server-llmling/watchers)
[](https://github.com/phil65/mcp-server-llmling/stars)
[](https://github.com/phil65/mcp-server-llmling)
[](https://github.com/phil65/mcp-server-llmling/commits)
[](https://github.com/phil65/mcp-server-llmling/releases)
[](https://github.com/phil65/mcp-server-llmling)
[](https://github.com/phil65/mcp-server-llmling)
[](https://codecov.io/gh/phil65/mcp-server-llmling/)
[](https://pyup.io/repos/github/phil65/mcp-server-llmling/)
[Read the documentation!](https://phil65.github.io/mcp-server-llmling/)
# LLMling Server Manual
## Overview
mcp-server-llmling is a server for the Machine Chat Protocol (MCP) that provides a YAML-based configuration system for LLM applications.
[LLMLing](https://phil65.github.io/LLMling/), the backend, provides a YAML-based configuration system for LLM applications.
It allows to set up custom MCP servers serving content defined in YAML files.
- **Static Declaration**: Define your LLM's environment in YAML - no code required
- **MCP Protocol**: Built on the Machine Chat Protocol (MCP) for standardized LLM interaction
- **Component Types**:
- **Resources**: Content providers (files, text, CLI output, etc.)
- **Prompts**: Message templates with arguments
- **Tools**: Python functions callable by the LLM
The YAML configuration creates a complete environment that provides the LLM with:
- Access to content via resources
- Structured prompts for consistent interaction
- Tools for extending capabilities
## Key Features
### 1. Resource Management
- Load and manage different types of resources:
- Text files (`PathResource`)
- Raw text content (`TextResource`)
- CLI command output (`CLIResource`)
- Python source code (`SourceResource`)
- Python callable results (`CallableResource`)
- Images (`ImageResource`)
- Support for resource watching/hot-reload
- Resource processing pipelines
- URI-based resource access
### 2. Tool System
- Register and execute Python functions as LLM tools
- Support for OpenAPI-based tools
- Entry point-based tool discovery
- Tool validation and parameter checking
- Structured tool responses
### 3. Prompt Management
- Static prompts with template support
- Dynamic prompts from Python functions
- File-based prompts
- Prompt argument validation
- Completion suggestions for prompt arguments
### 4. Multiple Transport Options
- Stdio-based communication (default)
- Server-Sent Events (SSE) / Streamable HTTP for web clients
- Support for custom transport implementations
## Usage
### With Zed Editor
Add LLMLing as a context server in your `settings.json`:
```json
{
"context_servers": {
"llmling": {
"command": {
"env": {},
"label": "llmling",
"path": "uvx",
"args": [
"mcp-server-llmling",
"start",
"path/to/your/config.yml"
]
},
"settings": {}
}
}
}
```
### With Claude Desktop
Configure LLMLing in your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"llmling": {
"command": "uvx",
"args": [
"mcp-server-llmling",
"start",
"path/to/your/config.yml"
],
"env": {}
}
}
}
```
### Manual Server Start
Start the server directly from command line:
```bash
# Latest version
uvx mcp-server-llmling@latest
```
### 1. Programmatic usage
```python
from llmling import RuntimeConfig
from mcp_server_llmling import LLMLingServer
async def main() -> None:
async with RuntimeConfig.open(config) as runtime:
server = LLMLingServer(runtime, enable_injection=True)
await server.start()
asyncio.run(main())
```
### 2. Using Custom Transport
```python
from llmling import RuntimeConfig
from mcp_server_llmling import LLMLingServer
async def main() -> None:
async with RuntimeConfig.open(config) as runtime:
server = LLMLingServer(
config,
transport="sse",
transport_options={
"host": "localhost",
"port": 3001,
"cors_origins": ["http://localhost:3000"]
}
)
await server.start()
asyncio.run(main())
```
### 3. Resource Configuration
```yaml
resources:
python_code:
type: path
path: "./src/**/*.py"
watch:
enabled: true
patterns:
- "*.py"
- "!**/__pycache__/**"
api_docs:
type: text
content: |
API Documentation
================
...
```
### 4. Tool Configuration
```yaml
tools:
analyze_code:
import_path: "mymodule.tools.analyze_code"
description: "Analyze Python code structure"
toolsets:
api:
type: openapi
spec: "https://api.example.com/openapi.json"
```
> [!TIP]
> For OpenAPI schemas, you can install [Redocly CLI](https://github.com/Redocly/redocly-cli) to bundle and resolve OpenAPI specifications before using them with LLMLing. This helps ensure your schema references are properly resolved and the specification is correctly formatted. If redocly is installed, it will be used automatically.
## Server Configuration
The server is configured through a YAML file with the following sections:
```yaml
global_settings:
timeout: 30
max_retries: 3
log_level: "INFO"
requirements: []
pip_index_url: null
extra_paths: []
resources:
# Resource definitions...
tools:
# Tool definitions...
toolsets:
# Toolset definitions...
prompts:
# Prompt definitions...
```
## MCP Protocol
The server implements the MCP protocol which supports:
1. **Resource Operations**
- List available resources
- Read resource content
- Watch for resource changes
2. **Tool Operations**
- List available tools
- Execute tools with parameters
- Get tool schemas
3. **Prompt Operations**
- List available prompts
- Get formatted prompts
- Get completions for prompt arguments
4. **Notifications**
- Resource changes
- Tool/prompt list updates
- Progress updates
- Log messages
Raw data
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"description": "# mcp-server-llmling\n\n[](https://pypi.org/project/mcp-server-llmling/)\n[](https://pypi.org/project/mcp-server-llmling/)\n[](https://pypi.org/project/mcp-server-llmling/)\n[](https://pypi.org/project/mcp-server-llmling/)\n[](https://pypi.org/project/mcp-server-llmling/)\n[](https://pypi.org/project/mcp-server-llmling/)\n[](https://pypi.org/project/mcp-server-llmling/)\n[](https://github.com/phil65/mcp-server-llmling/releases)\n[](https://github.com/phil65/mcp-server-llmling/graphs/contributors)\n[](https://github.com/phil65/mcp-server-llmling/discussions)\n[](https://github.com/phil65/mcp-server-llmling/forks)\n[](https://github.com/phil65/mcp-server-llmling/issues)\n[](https://github.com/phil65/mcp-server-llmling/pulls)\n[](https://github.com/phil65/mcp-server-llmling/watchers)\n[](https://github.com/phil65/mcp-server-llmling/stars)\n[](https://github.com/phil65/mcp-server-llmling)\n[](https://github.com/phil65/mcp-server-llmling/commits)\n[](https://github.com/phil65/mcp-server-llmling/releases)\n[](https://github.com/phil65/mcp-server-llmling)\n[](https://github.com/phil65/mcp-server-llmling)\n[](https://codecov.io/gh/phil65/mcp-server-llmling/)\n[](https://pyup.io/repos/github/phil65/mcp-server-llmling/)\n\n[Read the documentation!](https://phil65.github.io/mcp-server-llmling/)\n\n\n\n# LLMling Server Manual\n\n\n## Overview\n\nmcp-server-llmling is a server for the Machine Chat Protocol (MCP) that provides a YAML-based configuration system for LLM applications.\n\n[LLMLing](https://phil65.github.io/LLMling/), the backend, provides a YAML-based configuration system for LLM applications.\nIt allows to set up custom MCP servers serving content defined in YAML files.\n\n- **Static Declaration**: Define your LLM's environment in YAML - no code required\n- **MCP Protocol**: Built on the Machine Chat Protocol (MCP) for standardized LLM interaction\n- **Component Types**:\n - **Resources**: Content providers (files, text, CLI output, etc.)\n - **Prompts**: Message templates with arguments\n - **Tools**: Python functions callable by the LLM\n\nThe YAML configuration creates a complete environment that provides the LLM with:\n- Access to content via resources\n- Structured prompts for consistent interaction\n- Tools for extending capabilities\n\n\n## Key Features\n\n### 1. Resource Management\n- Load and manage different types of resources:\n - Text files (`PathResource`)\n - Raw text content (`TextResource`)\n - CLI command output (`CLIResource`)\n - Python source code (`SourceResource`)\n - Python callable results (`CallableResource`)\n - Images (`ImageResource`)\n- Support for resource watching/hot-reload\n- Resource processing pipelines\n- URI-based resource access\n\n### 2. Tool System\n- Register and execute Python functions as LLM tools\n- Support for OpenAPI-based tools\n- Entry point-based tool discovery\n- Tool validation and parameter checking\n- Structured tool responses\n\n### 3. Prompt Management\n- Static prompts with template support\n- Dynamic prompts from Python functions\n- File-based prompts\n- Prompt argument validation\n- Completion suggestions for prompt arguments\n\n### 4. Multiple Transport Options\n- Stdio-based communication (default)\n- Server-Sent Events (SSE) / Streamable HTTP for web clients\n- Support for custom transport implementations\n\n\n\n\n## Usage\n\n### With Zed Editor\n\nAdd LLMLing as a context server in your `settings.json`:\n\n```json\n{\n \"context_servers\": {\n \"llmling\": {\n \"command\": {\n \"env\": {},\n \"label\": \"llmling\",\n \"path\": \"uvx\",\n \"args\": [\n \"mcp-server-llmling\",\n \"start\",\n \"path/to/your/config.yml\"\n ]\n },\n \"settings\": {}\n }\n }\n}\n```\n\n### With Claude Desktop\n\nConfigure LLMLing in your `claude_desktop_config.json`:\n\n```json\n{\n \"mcpServers\": {\n \"llmling\": {\n \"command\": \"uvx\",\n \"args\": [\n \"mcp-server-llmling\",\n \"start\",\n \"path/to/your/config.yml\"\n ],\n \"env\": {}\n }\n }\n}\n```\n\n### Manual Server Start\n\nStart the server directly from command line:\n\n```bash\n# Latest version\nuvx mcp-server-llmling@latest\n```\n\n### 1. Programmatic usage\n\n```python\nfrom llmling import RuntimeConfig\nfrom mcp_server_llmling import LLMLingServer\n\nasync def main() -> None:\n async with RuntimeConfig.open(config) as runtime:\n server = LLMLingServer(runtime, enable_injection=True)\n await server.start()\n\nasyncio.run(main())\n```\n\n### 2. Using Custom Transport\n\n```python\nfrom llmling import RuntimeConfig\nfrom mcp_server_llmling import LLMLingServer\n\nasync def main() -> None:\n async with RuntimeConfig.open(config) as runtime:\n server = LLMLingServer(\n config,\n transport=\"sse\",\n transport_options={\n \"host\": \"localhost\",\n \"port\": 3001,\n \"cors_origins\": [\"http://localhost:3000\"]\n }\n )\n await server.start()\n\nasyncio.run(main())\n```\n\n### 3. Resource Configuration\n\n```yaml\nresources:\n python_code:\n type: path\n path: \"./src/**/*.py\"\n watch:\n enabled: true\n patterns:\n - \"*.py\"\n - \"!**/__pycache__/**\"\n\n api_docs:\n type: text\n content: |\n API Documentation\n ================\n ...\n```\n### 4. Tool Configuration\n\n```yaml\ntools:\n analyze_code:\n import_path: \"mymodule.tools.analyze_code\"\n description: \"Analyze Python code structure\"\n\ntoolsets:\n api:\n type: openapi\n spec: \"https://api.example.com/openapi.json\"\n```\n\n> [!TIP]\n> For OpenAPI schemas, you can install [Redocly CLI](https://github.com/Redocly/redocly-cli) to bundle and resolve OpenAPI specifications before using them with LLMLing. This helps ensure your schema references are properly resolved and the specification is correctly formatted. If redocly is installed, it will be used automatically.\n\n\n## Server Configuration\n\nThe server is configured through a YAML file with the following sections:\n\n```yaml\nglobal_settings:\n timeout: 30\n max_retries: 3\n log_level: \"INFO\"\n requirements: []\n pip_index_url: null\n extra_paths: []\n\nresources:\n # Resource definitions...\n\ntools:\n # Tool definitions...\n\ntoolsets:\n # Toolset definitions...\n\nprompts:\n # Prompt definitions...\n```\n\n## MCP Protocol\n\nThe server implements the MCP protocol which supports:\n\n1. **Resource Operations**\n - List available resources\n - Read resource content\n - Watch for resource changes\n\n2. **Tool Operations**\n - List available tools\n - Execute tools with parameters\n - Get tool schemas\n\n3. **Prompt Operations**\n - List available prompts\n - Get formatted prompts\n - Get completions for prompt arguments\n\n4. **Notifications**\n - Resource changes\n - Tool/prompt list updates\n - Progress updates\n - Log messages\n",
"bugtrack_url": null,
"license": "MIT License\n \n Copyright (c) 2024, Philipp Temminghoff\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in all\n copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.\n ",
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