vikingowl
9545a4b3ad
This commit completes Phase 10 of the MCP migration by removing all
direct provider usage from CLI/TUI and enforcing MCP-first architecture.
## Changes
### Core Architecture
- **main.rs**: Replaced OllamaProvider with RemoteMcpClient
- Uses MCP server configuration from config.toml if available
- Falls back to auto-discovery of MCP LLM server binary
- **agent_main.rs**: Unified provider and MCP client to single RemoteMcpClient
- Simplifies initialization with Arc::clone pattern
- All LLM communication now goes through MCP protocol
### Dependencies
- **Cargo.toml**: Removed owlen-ollama dependency from owlen-cli
- CLI no longer knows about Ollama implementation details
- Clean separation: only MCP servers use provider crates internally
### Tests
- **agent_tests.rs**: Updated all tests to use RemoteMcpClient
- Replaced OllamaProvider::new() with RemoteMcpClient::new()
- Updated test documentation to reflect MCP requirements
- All tests compile and run successfully
### Examples
- **Removed**: custom_provider.rs, basic_chat.rs (deprecated)
- **Added**: mcp_chat.rs - demonstrates recommended MCP-based usage
- Shows how to use RemoteMcpClient for LLM interactions
- Includes model listing and chat request examples
### Cleanup
- Removed outdated TODO about MCP integration (now complete)
- Updated comments to reflect current MCP architecture
## Architecture
```
CLI/TUI → RemoteMcpClient (impl Provider)
↓ MCP Protocol (STDIO/HTTP/WS)
MCP LLM Server → OllamaProvider → Ollama
```
## Benefits
- ✅ Clean separation of concerns
- ✅ CLI is protocol-agnostic (only knows MCP)
- ✅ Easier to add new LLM backends (just implement MCP server)
- ✅ All tests passing
- ✅ Full workspace builds successfully
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
72 lines
2.2 KiB
Rust
72 lines
2.2 KiB
Rust
//! Example demonstrating MCP-based chat interaction.
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//!
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//! This example shows the recommended way to interact with LLMs via the MCP architecture.
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//! It uses `RemoteMcpClient` which communicates with the MCP LLM server.
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//!
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//! Prerequisites:
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//! - Build the MCP LLM server: `cargo build --release -p owlen-mcp-llm-server`
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//! - Ensure Ollama is running with a model available
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use owlen_core::{
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mcp::remote_client::RemoteMcpClient,
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types::{ChatParameters, ChatRequest, Message, Role},
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Provider,
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};
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use std::sync::Arc;
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#[tokio::main]
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async fn main() -> Result<(), anyhow::Error> {
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println!("🦉 Owlen MCP Chat Example\n");
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// Create MCP client - this will spawn/connect to the MCP LLM server
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println!("Connecting to MCP LLM server...");
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let client = Arc::new(RemoteMcpClient::new()?);
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println!("✓ Connected\n");
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// List available models
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println!("Fetching available models...");
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let models = client.list_models().await?;
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println!("Available models:");
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for model in &models {
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println!(" - {} ({})", model.name, model.provider);
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}
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println!();
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// Select first available model or default
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let model_name = models
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.first()
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.map(|m| m.id.clone())
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.unwrap_or_else(|| "llama3.2:latest".to_string());
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println!("Using model: {}\n", model_name);
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// Create a simple chat request
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let user_message = "What is the capital of France? Please be concise.";
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println!("User: {}", user_message);
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let request = ChatRequest {
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model: model_name,
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messages: vec![Message::new(Role::User, user_message.to_string())],
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parameters: ChatParameters {
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temperature: Some(0.7),
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max_tokens: Some(100),
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stream: false,
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extra: std::collections::HashMap::new(),
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},
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tools: None,
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};
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// Send request and get response
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println!("\nAssistant: ");
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let response = client.chat(request).await?;
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println!("{}", response.message.content);
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if let Some(usage) = response.usage {
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println!(
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"\n📊 Tokens: {} prompt + {} completion = {} total",
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usage.prompt_tokens, usage.completion_tokens, usage.total_tokens
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);
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}
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Ok(())
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}
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