The Unichat MCP Server acts as a gateway to various AI models via the MCP protocol, enabling both general chat and specialized coding tasks.
Key capabilities:
Chat with multiple AI vendors: Send requests to OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek, Alibaba, and Inception using the unichat tool with system messages (context) and user messages (queries)
Code-specific tools: Review code, generate documentation, explain code functionality, and rework code using dedicated prompts
Integration options: Configure with Claude Desktop for seamless interaction
Deployment flexibility: Install via Smithery or build and publish manually
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Unichat MCP Server explain how this Python function works: def factorial(n): return 1 if n <= 1 else n * factorial(n-1)"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Send requests to OpenAI, Anthropic, and OpenAI-compatible providers using MCP protocol via tool or predefined prompts. For OpenAI-compatible providers such as MistralAI, xAI, Google AI, DeepSeek, Alibaba, or Inception, set UNICHAT_BASE_URL to the provider's compatible API endpoint.
Vendor API key required
The server implements one tool:
unichat: Send a request to unichat
Takes "messages" as required string arguments
Returns a response
code_review
Review code for best practices, potential issues, and improvements
Arguments:
code (string, required): The code to review"
document_code
Generate documentation for code including docstrings and comments
Arguments:
code (string, required): The code to comment"
explain_code
Explain how a piece of code works in detail
Arguments:
code (string, required): The code to explain"
code_rework
Apply requested changes to the provided code
Arguments:
changes (string, optional): The changes to apply"
code (string, required): The code to rework"
Related MCP server: MCP AI Gateway
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Supported Models:
A list of currently supported models to be used as
"SELECTED_UNICHAT_MODEL"may be found here. Please make sure to add the relevant vendor API key as"YOUR_UNICHAT_API_KEY"
Example:
"env": {
"UNICHAT_MODEL": "gpt-5.4-mini",
"UNICHAT_API_KEY": "YOUR_OPENAI_API_KEY"
}For OpenAI-compatible providers with custom endpoints:
"env": {
"UNICHAT_MODEL": "PROVIDER_MODEL",
"UNICHAT_API_KEY": "YOUR_PROVIDER_API_KEY",
"UNICHAT_BASE_URL": "https://provider.example.com/v1"
}When UNICHAT_BASE_URL is set, the server accepts the configured UNICHAT_MODEL without checking it against Unichat's built-in model list.
Development/Unpublished Servers Configuration
"mcpServers": {
"unichat-mcp-server": {
"command": "uv",
"args": [
"--directory",
"{{your source code local directory}}/unichat-mcp-server",
"run",
"unichat-mcp-server"
],
"env": {
"UNICHAT_MODEL": "SELECTED_UNICHAT_MODEL",
"UNICHAT_API_KEY": "YOUR_UNICHAT_API_KEY"
}
}
}Published Servers Configuration
"mcpServers": {
"unichat-mcp-server": {
"command": "uvx",
"args": [
"unichat-mcp-server"
],
"env": {
"UNICHAT_MODEL": "SELECTED_UNICHAT_MODEL",
"UNICHAT_API_KEY": "YOUR_UNICHAT_API_KEY"
}
}
}To install Unichat for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install unichat-mcp-server --client claudeTo prepare the package for distribution:
Remove older builds:
rm -rf distSync dependencies and update lockfile:
uv syncBuild package distributions:
uv buildThis will create source and wheel distributions in the dist/ directory.
Publish to PyPI:
uv publish --token {{YOUR_PYPI_API_TOKEN}}Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
npx @modelcontextprotocol/inspector uv --directory {{your source code local directory}}/unichat-mcp-server run unichat-mcp-serverUpon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
A hosted deployment is available on Fronteir AI.
Chat with an assistant. Example tool use message: Ask the unichat to review and evaluate your proposal.
| Name | Required | Description | Default |
|---|---|---|---|
| messages | Yes | Array of exactly two messages: first a system message defining the task, then a user message with the specific query |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions nothing about behavioral traits like whether this is a read-only operation, if it requires authentication, rate limits, or what kind of responses to expect. The example hints at evaluation tasks but doesn't disclose operational characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief but includes an example that adds some value. However, the formatting with extra whitespace is awkward, and the example could be integrated more cleanly. It's not excessively verbose, but the structure could be improved for better front-loading of information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a chat tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the assistant does, what domains it covers, what format responses take, or any limitations. The example provides minimal context but doesn't compensate for the lack of structured information about this interactive tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the single parameter (messages array with exactly two messages). The description adds no parameter information beyond what's in the schema, not even mentioning the two-message requirement. Baseline 3 is appropriate when schema does all the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Chat with an assistant' which indicates the basic function, but it's vague about what this assistant does or what domain it operates in. The example tool use message adds some context about reviewing proposals, but doesn't make the purpose specific or distinguish it from other chat tools. It's not tautological but lacks clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives is provided. The example suggests it can be used for reviewing proposals, but there's no mention of prerequisites, limitations, or when not to use it. With no sibling tools, the bar is lower, but still lacks basic usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'unichat' has a clear and distinct purpose of chatting with an assistant.
A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'unichat' follows a simple, readable pattern without any conflicting conventions.
A single tool is too few for most server purposes, as it severely limits functionality and scope. While it might be appropriate for a minimal chat interface, it feels thin and lacks the depth expected for a typical MCP server, which usually requires multiple tools to handle different operations or resources.
For a chat assistant domain, the single tool 'unichat' covers the core action of chatting, but there are notable gaps. It lacks operations for managing chat history, configuring settings, or handling multiple sessions, which are common in chat systems. However, the basic functionality is present, allowing agents to perform the primary task.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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