chore: remove dead code and unused token counter package

- Delete dead ESC listener code and bubbletea/time imports from agent
- Remove internal/tokens/ package (empty stubs and trivial estimator)
- Inline token estimation into usage_tracker as unexported helper
- Remove unused EstimateAndUpdateUsageFromText dead method
- Remove 9 unsupported provider env var entries from registry

cmd/root.go

@@ -16,7 +16,6 @@ import (
 	"github.com/mark3labs/mcphost/internal/hooks"
 	"github.com/mark3labs/mcphost/internal/models"
 	"github.com/mark3labs/mcphost/internal/session"
-	"github.com/mark3labs/mcphost/internal/tokens"
 	"github.com/mark3labs/mcphost/internal/tools"
 	"github.com/mark3labs/mcphost/internal/ui"
 	"github.com/spf13/cobra"
@@ -362,9 +361,6 @@ func runMCPHost(ctx context.Context) error {
 }
 
 func runNormalMode(ctx context.Context) error {
-	// Initialize token counters
-	tokens.InitializeTokenCounters()
-
 	// Validate flag combinations
 	if quietFlag && promptFlag == "" {
 		return fmt.Errorf("--quiet flag can only be used with --prompt/-p")

internal/agent/agent.go

@@ -4,9 +4,7 @@ import (
 	"context"
 	"encoding/json"
 	"fmt"
-	"time"
 
-	tea "charm.land/bubbletea/v2"
 	"charm.land/fantasy"
 
 	"github.com/mark3labs/mcphost/internal/config"
@@ -355,72 +353,3 @@ func (a *Agent) GetModel() fantasy.LanguageModel {
 func (a *Agent) Close() error {
 	return a.toolManager.Close()
 }
-
-// escListenerModel is a simple Bubble Tea model for ESC key detection
-type escListenerModel struct {
-	escPressed chan bool
-}
-
-func (m escListenerModel) Init() tea.Cmd {
-	return nil
-}
-
-func (m escListenerModel) Update(msg tea.Msg) (tea.Model, tea.Cmd) {
-	if msg, ok := msg.(tea.KeyPressMsg); ok {
-		if msg.String() == "esc" {
-			select {
-			case m.escPressed <- true:
-			default:
-			}
-			return m, tea.Quit
-		}
-	}
-	return m, nil
-}
-
-func (m escListenerModel) View() tea.View {
-	return tea.NewView("")
-}
-
-// listenForESC listens for ESC key press using Bubble Tea and returns true if detected
-func (a *Agent) listenForESC(stopChan chan bool, readyChan chan bool) bool {
-	escPressed := make(chan bool, 1)
-
-	model := escListenerModel{
-		escPressed: escPressed,
-	}
-
-	p := tea.NewProgram(model, tea.WithoutRenderer())
-
-	go func() {
-		if _, err := p.Run(); err != nil {
-			select {
-			case escPressed <- false:
-			default:
-			}
-		}
-	}()
-
-	go func() {
-		time.Sleep(10 * time.Millisecond)
-		select {
-		case readyChan <- true:
-		default:
-		}
-	}()
-
-	select {
-	case <-stopChan:
-		p.Kill()
-		time.Sleep(50 * time.Millisecond)
-		return false
-	case pressed := <-escPressed:
-		p.Kill()
-		time.Sleep(50 * time.Millisecond)
-		return pressed
-	case <-time.After(30 * time.Second):
-		p.Kill()
-		time.Sleep(50 * time.Millisecond)
-		return false
-	}
-}

internal/models/registry.go

@@ -53,15 +53,6 @@ var providerEnvVars = map[string][]string{
 	"bedrock":                 {"AWS_ACCESS_KEY_ID"},
 	"google-vertex-anthropic": {"GOOGLE_APPLICATION_CREDENTIALS"},
 	"ollama":                  {},
-	"mistral":                 {"MISTRAL_API_KEY"},
-	"groq":                    {"GROQ_API_KEY"},
-	"deepseek":                {"DEEPSEEK_API_KEY"},
-	"xai":                     {"XAI_API_KEY"},
-	"fireworks":               {"FIREWORKS_API_KEY"},
-	"together":                {"TOGETHER_API_KEY"},
-	"perplexity":              {"PERPLEXITY_API_KEY"},
-	"alibaba":                 {"DASHSCOPE_API_KEY"},
-	"cohere":                  {"COHERE_API_KEY"},
 }
 
 // ModelsRegistry provides validation and information about models.

internal/tokens/anthropic.go

@@ -1,16 +0,0 @@
-// Package tokens provides token counting and estimation functionality for
-// various language model providers. It includes utilities for estimating
-// token counts in text, as well as provider-specific implementations for
-// more accurate token counting.
-//
-// The package supports multiple approaches to token counting:
-//   - Quick estimation using character-based heuristics
-//   - Provider-specific tokenizers for accurate counts
-//   - Initialization functions for setting up token counters
-//
-// Token counting is essential for:
-//   - Managing API rate limits
-//   - Calculating costs for API usage
-//   - Ensuring prompts fit within model context windows
-//   - Optimizing prompt engineering and response handling
-package tokens

internal/tokens/counter.go

@@ -1,24 +0,0 @@
-package tokens
-
-// EstimateTokens estimates the number of tokens in the given text string.
-// It uses a rough approximation of 4 characters per token, which is a common
-// heuristic for most language models. This function provides a quick estimation
-// without requiring model-specific tokenizers.
-//
-// The estimation may not be accurate for all models or text types, particularly
-// for texts with many special characters, non-English languages, or code snippets.
-// For more accurate token counting, use model-specific tokenizers when available.
-//
-// Parameters:
-//   - text: The input text string to estimate tokens for
-//
-// Returns:
-//   - int: The estimated number of tokens in the text
-//
-// Example:
-//
-//	count := EstimateTokens("Hello, world!")  // Returns approximately 3
-func EstimateTokens(text string) int {
-	// Rough approximation: ~4 characters per token for most models
-	return len(text) / 4
-}

internal/tokens/init.go

@@ -1,52 +0,0 @@
-package tokens
-
-// InitializeTokenCounters registers all available token counters for various
-// language model providers. This function should be called during application
-// startup to ensure that token counting functionality is available for all
-// supported models.
-//
-// Currently, this function is a placeholder for future provider-specific
-// token counter implementations. As new providers are added (OpenAI, Anthropic,
-// Google, etc.), their respective token counters will be registered here.
-//
-// This function does not require any API keys and will only initialize
-// counters that can work without authentication.
-//
-// Example:
-//
-//	func main() {
-//	    tokens.InitializeTokenCounters()
-//	    // Token counting is now available
-//	}
-func InitializeTokenCounters() {
-	// Future provider-specific counters can be registered here
-}
-
-// InitializeTokenCountersWithKeys registers token counters for various language
-// model providers using the provided API keys. This function enables more
-// accurate token counting by allowing access to provider-specific tokenization
-// endpoints or libraries that require authentication.
-//
-// This function should be called during application startup after API keys
-// have been loaded from configuration or environment variables. It will
-// initialize token counters for providers where API keys are available,
-// enabling precise token counting that matches the provider's actual
-// tokenization logic.
-//
-// The function will silently skip providers for which no API keys are
-// configured, allowing the application to continue with partial token
-// counting capabilities.
-//
-// Future implementations will accept provider-specific API keys through
-// parameters or read them from a configuration context.
-//
-// Example:
-//
-//	func main() {
-//	    // Load API keys from environment or config
-//	    tokens.InitializeTokenCountersWithKeys()
-//	    // Provider-specific token counting is now available
-//	}
-func InitializeTokenCountersWithKeys() {
-	// Future provider-specific counters can be registered here
-}

internal/ui/usage_tracker.go

@@ -8,7 +8,6 @@ import (
 	"image/color"
 
 	"github.com/mark3labs/mcphost/internal/models"
-	"github.com/mark3labs/mcphost/internal/tokens"
 )
 
 // UsageStats encapsulates detailed token usage and cost breakdown for a single
@@ -64,13 +63,9 @@ func NewUsageTracker(modelInfo *models.ModelInfo, provider string, width int, is
 	}
 }
 
-// EstimateTokens provides a rough estimate of the number of tokens in the given text.
-// This uses a simple heuristic of approximately 4 characters per token, which is a
-// reasonable approximation for most models but not precise. Actual token counts may vary
-// significantly based on the specific tokenizer used by each model.
-func EstimateTokens(text string) int {
-	// Rough approximation: ~4 characters per token for most models
-	// This is not accurate but gives a reasonable estimate
+// estimateTokens provides a rough estimate of the number of tokens in the given text.
+// Uses a simple heuristic of ~4 characters per token.
+func estimateTokens(text string) int {
 	return len(text) / 4
 }
 
@@ -126,16 +121,8 @@ func (ut *UsageTracker) UpdateUsage(inputTokens, outputTokens, cacheReadTokens,
 // the usage statistics. This method is used when actual token counts are not available
 // from the API response.
 func (ut *UsageTracker) EstimateAndUpdateUsage(inputText, outputText string) {
-	inputTokens := tokens.EstimateTokens(inputText)
-	outputTokens := tokens.EstimateTokens(outputText)
-	ut.UpdateUsage(inputTokens, outputTokens, 0, 0)
-}
-
-// EstimateAndUpdateUsageFromText is an alias for EstimateAndUpdateUsage, providing
-// backward compatibility. It estimates token counts from text and updates usage statistics.
-func (ut *UsageTracker) EstimateAndUpdateUsageFromText(inputText, outputText string) {
-	inputTokens := tokens.EstimateTokens(inputText)
-	outputTokens := tokens.EstimateTokens(outputText)
+	inputTokens := estimateTokens(inputText)
+	outputTokens := estimateTokens(outputText)
 	ut.UpdateUsage(inputTokens, outputTokens, 0, 0)
 }