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pal-mcp-server

The power of Claude Code / GeminiCLI / CodexCLI + [Gemini / OpenAI / OpenRouter / Azure / Grok / Ollama / Custom Model / All Of The Above] working as one.

BeehiveInnovationsBeehiveInnovations
82/ 100

公开评测 · 综合采用结论

证据充分,整体质量与安全表现优秀

查看评测依据 评测我的项目基于公开项目证据,非安全认证或安装推荐
11.8kstars
1.0kforks
最近更新 9个月前
评测生成时间(北京时间)
本报告引擎
v3.10.0
当前引擎
v3.16.0

本报告与当前引擎使用不同规则;原分数不会自动更新,不同版本的分数不宜直接对比。

重新评测此项目

进入后确认来源与额度,提交才会创建任务。

Evaluation report

综合采用结论

82
B
满分 100
值得推荐低风险
决策摘要

证据充分,整体质量与安全表现优秀

100%
高置信度
100
文档
100
安全
80
质量
30
活跃
67
采用
  • 基础评测完成+25/25确定性评分与静态安全扫描已完成
  • README 有效证据+25/2519,408 个去重后的有效字符
  • 独立证据来源+20/206 类非重复证据,重复文件不叠加
  • 仓库元数据+10/10已取得仓库状态与采用数据
  • 活跃记录+5/5已取得最近提交时间
  • AI 复核+15/15已完成结构化 AI 证据复核
How it works · 时序图

PAL MCP 多模型协作流程

README 描述了用户 CLI 与多个外部模型之间的请求-响应交互,存在明确的调用顺序和上下文传递。

AI 提取 · 证据约束

左右滑动查看完整图示

PAL MCP 多模型协作流程README 描述了用户 CLI 与多个外部模型之间的请求-响应交互,存在明确的调用顺序和上下文传递。用户发起者CLI编排者PAL MCP代理层模型1外部模型模型2外部模型发起请求调用工具请求分析返回结果请求复审返回结果汇总结果呈现输出
图示依据
  • • Example Workflows 描述 codereview 流程:Claude 协调 Gemini Pro 和 O3
  • • clink 工具支持 CLI 子代理,上下文隔离
  • • Conversation continuity 功能确保上下文跨工具传递
五维表现
PAL MCP 提供多模型编排与上下文延续,解决真实开发协作需求,示例丰富。主要缺口是部分工具默认禁用且配置细节依赖外部文档,但整体证据充分。
质量证据
  • Quick Start 提供两种安装方式:./run-server.sh 和 uvx 配置
  • Core Tools 列出 14 个工具,并标注默认启用/禁用状态
  • Tool Configuration 章节展示 DISABLED_TOOLS 环境变量配置
  • Example Workflows 展示多模型代码审查和调试的具体提示词
  • License 章节声明 Apache 2.0
采用建议
优势
  • 问题与用途描述
  • 有效 README
  • 安装或接入步骤
  • 可执行示例
  • 未发现已知高风险模式
关注点
  • 部分工具默认禁用,需额外配置才能使用全部功能
  • 配置依赖外部文档,README 中未完整展示所有参数
  • 错误处理与排障信息未在 README 中直接体现
  • 安全边界与权限细节未明确说明
适合

需要多模型协作的 CLI 用户(Claude Code、Codex 等)、希望进行多模型代码审查和调试的开发者、需要上下文延续和模型切换的复杂工作流、使用多种 AI 提供商(Gemini、OpenAI、Ollama 等)的团队

不建议直接用于

仅需单一模型简单调用的用户(可能过度复杂)、对上下文窗口占用敏感且不需要多模型功能的场景

也有自己的公开项目?先看完证据,再用当前规则生成独立报告。

评测我的项目 →
文档证据
100/100
问题与用途描述10 分
有效 README12 分
安装或接入步骤14 分
可执行示例16 分
输入、参数或工具说明11 分
输出或结果说明9 分
限制、权限或边界12 分
错误处理或排障8 分
许可证信息5 分
结构化章节3 分
安全证据
低风险
未发现已知高风险模式

静态扫描不是安全保证,生产接入前仍应人工复核权限和数据边界。

方法、证据与局限展开
数据来源

GitHub Repository API

扫描范围

7 个文件 · 44,874 字符

评测引擎

v3.10.0 · AI 复核已启用(deepseek-chat)

局限
  • 静态评测不会安装或执行项目代码
  • 安全扫描基于高信号文件与已知模式,不能替代人工审计
  • 流行度只反映采用程度,不代表安全或工程质量

30 天热度趋势

README

PAL MCP: Many Workflows. One Context.

Your AI's PAL – a Provider Abstraction Layer
Formerly known as Zen MCP

PAL in action

👉 Watch more examples

Your CLI + Multiple Models = Your AI Dev Team

Use the 🤖 CLI you love:
Claude Code · Gemini CLI · Codex CLI · Qwen Code CLI · Cursor · and more

With multiple models within a single prompt:
Gemini · OpenAI · Anthropic · Grok · Azure · Ollama · OpenRouter · DIAL · On-Device Model


🆕 Now with CLI-to-CLI Bridge

The new clink (CLI + Link) tool connects external AI CLIs directly into your workflow:

  • Connect external CLIs like Gemini CLI, Codex CLI, and Claude Code directly into your workflow
  • CLI Subagents - Launch isolated CLI instances from within your current CLI! Claude Code can spawn Codex subagents, Codex can spawn Gemini CLI subagents, etc. Offload heavy tasks (code reviews, bug hunting) to fresh contexts while your main session's context window remains unpolluted. Each subagent returns only final results.
  • Context Isolation - Run separate investigations without polluting your primary workspace
  • Role Specialization - Spawn planner, codereviewer, or custom role agents with specialized system prompts
  • Full CLI Capabilities - Web search, file inspection, MCP tool access, latest documentation lookups
  • Seamless Continuity - Sub-CLIs participate as first-class members with full conversation context between tools
# Codex spawns Codex subagent for isolated code review in fresh context
clink with codex codereviewer to audit auth module for security issues
# Subagent reviews in isolation, returns final report without cluttering your context as codex reads each file and walks the directory structure

# Consensus from different AI models → Implementation handoff with full context preservation between tools
Use consensus with gpt-5 and gemini-pro to decide: dark mode or offline support next
Continue with clink gemini - implement the recommended feature
# Gemini receives full debate context and starts coding immediately

👉 Learn more about clink


Why PAL MCP?

Why rely on one AI model when you can orchestrate them all?

A Model Context Protocol server that supercharges tools like Claude Code, Codex CLI, and IDE clients such as Cursor or the Claude Dev VS Code extension. PAL MCP connects your favorite AI tool to multiple AI models for enhanced code analysis, problem-solving, and collaborative development.

True AI Collaboration with Conversation Continuity

PAL supports conversation threading so your CLI can discuss ideas with multiple AI models, exchange reasoning, get second opinions, and even run collaborative debates between models to help you reach deeper insights and better solutions.

Your CLI always stays in control but gets perspectives from the best AI for each subtask. Context carries forward seamlessly across tools and models, enabling complex workflows like: code reviews with multiple models → automated planning → implementation → pre-commit validation.

You're in control. Your CLI of choice orchestrates the AI team, but you decide the workflow. Craft powerful prompts that bring in Gemini Pro, GPT 5, Flash, or local offline models exactly when needed.

Reasons to Use PAL MCP

A typical workflow with Claude Code as an example:

  1. Multi-Model Orchestration - Claude coordinates with Gemini Pro, O3, GPT-5, and 50+ other models to get the best analysis for each task

  2. Context Revival Magic - Even after Claude's context resets, continue conversations seamlessly by having other models "remind" Claude of the discussion

  3. Guided Workflows - Enforces systematic investigation phases that prevent rushed analysis and ensure thorough code examination

  4. Extended Context Windows - Break Claude's limits by delegating to Gemini (1M tokens) or O3 (200K tokens) for massive codebases

  5. True Conversation Continuity - Full context flows across tools and models - Gemini remembers what O3 said 10 steps ago

  6. Model-Specific Strengths - Extended thinking with Gemini Pro, blazing speed with Flash, strong reasoning with O3, privacy with local Ollama

  7. Professional Code Reviews - Multi-pass analysis with severity levels, actionable feedback, and consensus from multiple AI experts

  8. Smart Debugging Assistant - Systematic root cause analysis with hypothesis tracking and confidence levels

  9. Automatic Model Selection - Claude intelligently picks the right model for each subtask (or you can specify)

  10. Vision Capabilities - Analyze screenshots, diagrams, and visual content with vision-enabled models

  11. Local Model Support - Run Llama, Mistral, or other models locally for complete privacy and zero API costs

  12. Bypass MCP Token Limits - Automatically works around MCP's 25K limit for large prompts and responses

The Killer Feature: When Claude's context resets, just ask to "continue with O3" - the other model's response magically revives Claude's understanding without re-ingesting documents!

Example: Multi-Model Code Review Workflow

  1. Perform a codereview using gemini pro and o3 and use planner to generate a detailed plan, implement the fixes and do a final precommit check by continuing from the previous codereview
  2. This triggers a codereview workflow where Claude walks the code, looking for all kinds of issues
  3. After multiple passes, collects relevant code and makes note of issues along the way
  4. Maintains a confidence level between exploring, low, medium, high and certain to track how confidently it's been able to find and identify issues
  5. Generates a detailed list of critical -> low issues
  6. Shares the relevant files, findings, etc with Gemini Pro to perform a deep dive for a second codereview
  7. Comes back with a response and next does the same with o3, adding to the prompt if a new discovery comes to light
  8. When done, Claude takes in all the feedback and combines a single list of all critical -> low issues, including good patterns in your code. The final list includes new findings or revisions in case Claude misunderstood or missed something crucial and one of the other models pointed this out
  9. It then uses the planner workflow to break the work down into simpler steps if a major refactor is required
  10. Claude then performs the actual work of fixing highlighted issues
  11. When done, Claude returns to Gemini Pro for a precommit review

All within a single conversation thread! Gemini Pro in step 11 knows what was recommended by O3 in step 7! Taking that context and review into consideration to aid with its final pre-commit review.

Think of it as Claude Code for Claude Code. This MCP isn't magic. It's just super-glue.

Remember: Claude stays in full control — but YOU call the shots. PAL is designed to have Claude engage other models only when needed — and to follow through with meaningful back-and-forth. You're the one who crafts the powerful prompt that makes Claude bring in Gemini, Flash, O3 — or fly solo. You're the guide. The prompter. The puppeteer.

You are the AI - Actually Intelligent.

Recommended AI Stack

For Claude Code Users

For best results when using Claude Code:

  • Sonnet 4.5 - All agentic work and orchestration
  • Gemini 3.0 Pro OR GPT-5.2 / Pro - Deep thinking, additional code reviews, debugging and validations, pre-commit analysis
For Codex Users

For best results when using Codex CLI:

  • GPT-5.2 Codex Medium - All agentic work and orchestration
  • Gemini 3.0 Pro OR GPT-5.2-Pro - Deep thinking, additional code reviews, debugging and validations, pre-commit analysis

Quick Start (5 minutes)

Prerequisites: Python 3.10+, Git, uv installed

1. Get API Keys (choose one or more):

  • OpenRouter - Access multiple models with one API
  • Gemini - Google's latest models
  • OpenAI - O3, GPT-5 series
  • Azure OpenAI - Enterprise deployments of GPT-4o, GPT-4.1, GPT-5 family
  • X.AI - Grok models
  • DIAL - Vendor-agnostic model access
  • Ollama - Local models (free)

2. Install (choose one):

Option A: Clone and Automatic Setup (recommended)

git clone https://github.com/BeehiveInnovations/pal-mcp-server.git
cd pal-mcp-server

# Handles everything: setup, config, API keys from system environment. 
# Auto-configures Claude Desktop, Claude Code, Gemini CLI, Codex CLI, Qwen CLI
# Enable / disable additional settings in .env
./run-server.sh  

Option B: Instant Setup with uvx

// Add to ~/.claude/settings.json or .mcp.json
// Don't forget to add your API keys under env
{
  "mcpServers": {
    "pal": {
      "command": "bash",
      "args": ["-c", "for p in $(which uvx 2>/dev/null) $HOME/.local/bin/uvx /opt/homebrew/bin/uvx /usr/local/bin/uvx uvx; do [ -x \"$p\" ] && exec \"$p\" --from git+https://github.com/BeehiveInnovations/pal-mcp-server.git pal-mcp-server; done; echo 'uvx not found' >&2; exit 1"],
      "env": {
        "PATH": "/usr/local/bin:/usr/bin:/bin:/opt/homebrew/bin:~/.local/bin",
        "GEMINI_API_KEY": "your-key-here",
        "DISABLED_TOOLS": "analyze,refactor,testgen,secaudit,docgen,tracer",
        "DEFAULT_MODEL": "auto"
      }
    }
  }
}

3. Start Using!

"Use pal to analyze this code for security issues with gemini pro"
"Debug this error with o3 and then get flash to suggest optimizations"
"Plan the migration strategy with pal, get consensus from multiple models"
"clink with cli_name=\"gemini\" role=\"planner\" to draft a phased rollout plan"

👉 Complete Setup Guide with detailed installation, configuration for Gemini / Codex / Qwen, and troubleshooting 👉 Cursor & VS Code Setup for IDE integration instructions 📺 Watch tools in action to see real-world examples

Provider Configuration

PAL activates any provider that has credentials in your .env. See .env.example for deeper customization.

Core Tools

Note: Each tool comes with its own multi-step workflow, parameters, and descriptions that consume valuable context window space even when not in use. To optimize performance, some tools are disabled by default. See Tool Configuration below to enable them.

Collaboration & Planning (Enabled by default)

  • clink - Bridge requests to external AI CLIs (Gemini planner, codereviewer, etc.)
  • chat - Brainstorm ideas, get second opinions, validate approaches. With capable models (GPT-5.2 Pro, Gemini 3.0 Pro), generates complete code / implementation
  • thinkdeep - Extended reasoning, edge case analysis, alternative perspectives
  • planner - Break down complex projects into structured, actionable plans
  • consensus - Get expert opinions from multiple AI models with stance steering

Code Analysis & Quality

  • debug - Systematic investigation and root cause analysis
  • precommit - Validate changes before committing, prevent regressions
  • codereview - Professional reviews with severity levels and actionable feedback
  • analyze (disabled by default - enable) - Understand architecture, patterns, dependencies across entire codebases

Development Tools (Disabled by default - enable)

  • refactor - Intelligent code refactoring with decomposition focus
  • testgen - Comprehensive test generation with edge cases
  • secaudit - Security audits with OWASP Top 10 analysis
  • docgen - Generate documentation with complexity analysis

Utilities

  • apilookup - Forces current-year API/SDK documentation lookups in a sub-process (saves tokens within the current context window), prevents outdated training data responses
  • challenge - Prevent "You're absolutely right!" responses with critical analysis
  • tracer (disabled by default - enable) - Static analysis prompts for call-flow mapping
👉 Tool Configuration

Default Configuration

To optimize context window usage, only essential tools are enabled by default:

Enabled by default:

  • chat, thinkdeep, planner, consensus - Core collaboration tools
  • codereview, precommit, debug - Essential code quality tools
  • apilookup - Rapid API/SDK information lookup
  • challenge - Critical thinking utility

Disabled by default:

  • analyze, refactor, testgen, secaudit, docgen, tracer

Enabling Additional Tools

To enable additional tools, remove them from the DISABLED_TOOLS list:

Option 1: Edit your .env file

# Default configuration (from .env.example)
DISABLED_TOOLS=analyze,refactor,testgen,secaudit,docgen,tracer

# To enable specific tools, remove them from the list
# Example: Enable analyze tool
DISABLED_TOOLS=refactor,testgen,secaudit,docgen,tracer

# To enable ALL tools
DISABLED_TOOLS=

Option 2: Configure in MCP settings

// In ~/.claude/settings.json or .mcp.json
{
  "mcpServers": {
    "pal": {
      "env": {
        // Tool configuration
        "DISABLED_TOOLS": "refactor,testgen,secaudit,docgen,tracer",
        "DEFAULT_MODEL": "pro",
        "DEFAULT_THINKING_MODE_THINKDEEP": "high",
        
        // API configuration
        "GEMINI_API_KEY": "your-gemini-key",
        "OPENAI_API_KEY": "your-openai-key",
        "OPENROUTER_API_KEY": "your-openrouter-key",
        
        // Logging and performance
        "LOG_LEVEL": "INFO",
        "CONVERSATION_TIMEOUT_HOURS": "6",
        "MAX_CONVERSATION_TURNS": "50"
      }
    }
  }
}

Option 3: Enable all tools

// Remove or empty the DISABLED_TOOLS to enable everything
{
  "mcpServers": {
    "pal": {
      "env": {
        "DISABLED_TOOLS": ""
      }
    }
  }
}

Note:

  • Essential tools (version, listmodels) cannot be disabled
  • After changing tool configuration, restart your Claude session for changes to take effect
  • Each tool adds to context window usage, so only enable what you need

📺 Watch Tools In Action

Chat Tool - Collaborative decision making and multi-turn conversations

Picking Redis vs Memcached:

Chat Redis or Memcached_web.webm

Multi-turn conversation with continuation:

Chat With Gemini_web.webm

Consensus Tool - Multi-model debate and decision making

Multi-model consensus debate:

PAL Consensus Debate

PreCommit Tool - Comprehensive change validation

Pre-commit validation workflow:

README 图片
API Lookup Tool - Current vs outdated API documentation

Without PAL - outdated APIs:

API without PAL

With PAL - current APIs:

API with PAL

Challenge Tool - Critical thinking vs reflexive agreement

Without PAL:

without_pal@2x

With PAL:

with_pal@2x

Key Features

AI Orchestration

  • Auto model selection - Claude picks the right AI for each task
  • Multi-model workflows - Chain different models in single conversations
  • Conversation continuity - Context preserved across tools and models
  • Context revival - Continue conversations even after context resets

Model Support

  • Multiple providers - Gemini, OpenAI, Azure, X.AI, OpenRouter, DIAL, Ollama
  • Latest models - GPT-5, Gemini 3.0 Pro, O3, Grok-4, local Llama
  • Thinking modes - Control reasoning depth vs cost
  • Vision support - Analyze images, diagrams, screenshots

Developer Experience

  • Guided workflows - Systematic investigation prevents rushed analysis
  • Smart file handling - Auto-expand directories, manage token limits
  • Web search integration - Access current documentation and best practices
  • Large prompt support - Bypass MCP's 25K token limit

Example Workflows

Multi-model Code Review:

"Perform a codereview using gemini pro and o3, then use planner to create a fix strategy"

→ Claude reviews code systematically → Consults Gemini Pro → Gets O3's perspective → Creates unified action plan

Collaborative Debugging:

"Debug this race condition with max thinking mode, then validate the fix with precommit"

→ Deep investigation → Expert analysis → Solution implementation → Pre-commit validation

Architecture Planning:

"Plan our microservices migration, get consensus from pro and o3 on the approach"

→ Structured planning → Multiple expert opinions → Consensus building → Implementation roadmap

👉 Advanced Usage Guide for complex workflows, model configuration, and power-user features

Quick Links

📖 Documentation

🔧 Setup & Support

License

Apache 2.0 License - see LICENSE file for details.

Acknowledgments

Built with the power of Multi-Model AI collaboration 🤝

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