| name | cercano-local |
| description | Run prompts against local AI models via Cercano and Ollama. Use this for local inference — faster, private, and zero cost. Handles chat-style queries and agentic code generation with automatic validation. Offload summarization, explanation, code writing, and general LLM tasks to a local model instead of sending them to the cloud. |
| compatibility | Requires Cercano server running and connected to an Ollama instance. |
Cercano Local Inference
Run prompts against local AI models through Cercano's MCP interface. Cercano routes requests to Ollama for local inference.
MCP Tool
Tool name: cercano_local
Parameters
| Parameter | Type | Required | Description |
|---|
prompt | string | Yes | The prompt to run against local models. |
file_path | string | No | Target file path for code changes. When provided with work_dir, enables the agentic code generation loop with validation. |
work_dir | string | No | Working directory for code validation (go build/test). When provided with file_path, enables the agentic code generation loop. |
context | string | No | Additional context such as existing code or file contents. |
conversation_id | string | No | Conversation ID for multi-turn support across calls. |
Modes
Chat Mode
Provide only prompt (and optionally context) for a direct LLM call. The response is the model's text output.
Agentic Code Generation Mode
Provide prompt, file_path, and work_dir to enable a generate-validate loop. Cercano will:
- Generate code based on the prompt
- Write it to the target file
- Run validation (build/test) in the working directory
- If validation fails, self-correct and retry
Examples
Chat query:
{
"prompt": "What are the SOLID principles in software design?"
}
Code generation with context:
{
"prompt": "Add error handling to this function",
"file_path": "internal/handler/auth.go",
"work_dir": "/project",
"context": "func Login(w http.ResponseWriter, r *http.Request) { ... }"
}
Multi-turn conversation:
{
"prompt": "Now refactor that to use the repository pattern",
"conversation_id": "conv-abc123"
}