AWS FinOps MCP Server

AWS FinOps MCP Server

Provides a comprehensive suite of 76 tools for AWS cloud resource optimization, cost management, and infrastructure monitoring. It enables users to identify unused resources, analyze cost trends, right-size capacity, and maintain security compliance through natural language.

Category
访问服务器

README

AWS FinOps MCP Server

Production-Ready Deployment: This MCP server is optimized for deployment on Amazon Bedrock AgentCore Runtime

Model Context Protocol (MCP) server for AWS Financial Operations (FinOps) - providing comprehensive tools for cloud resource optimization, cost management, and performance monitoring.

🚀 Quick Start - Deploy to AWS

Deploy to Amazon Bedrock AgentCore (Recommended)

Deploy your MCP server to production in minutes:

# 1. Create ECR repository
./create-ecr-repo.sh

# 2. Update configuration
sed -i 's/ecr: auto/ecr: aws-pillar-mcp-server/' .bedrock_agentcore.yaml

# 3. Deploy to AWS
agentcore launch

# 4. Test your deployment
agentcore invoke '{"prompt": "find unused resources in us-east-1"}'

📖 Complete Deployment Guides:

Local Development

# Install dependencies
pip install -e .

# Run locally
python -m aws_finops_mcp

🎯 Quick Overview

  • 76 Tools across 14 categories for comprehensive AWS optimization
  • Category Filtering - Load only the tools you need (NEW!)
  • Dual Modes - stdio for direct integration, HTTP for remote access
  • Cost Savings - Identify unused resources and optimization opportunities
  • Security & Compliance - Find unencrypted resources and security issues
  • Performance Analysis - Analyze and optimize application performance
  • Ready-to-Use IAM Policies - Get started in minutes

📊 View Architecture Diagrams - Visual system architecture and data flows

🆕 What's New

Category-Based Tool Filtering

Problem: Loading all 76 tools can be slow and overwhelming for MCP clients.

Solution: Use MCP_TOOL_CATEGORIES to enable only the categories you need!

# Load only cost and cleanup tools (25 tools instead of 76)
export MCP_TOOL_CATEGORIES="cleanup,cost"
python -m aws_finops_mcp

# 67% reduction in tool count, faster loading, easier navigation

Benefits:

  • 67-89% faster loading for focused use cases
  • 🎯 Better organization - see only relevant tools
  • 🔧 Flexible - change categories without code changes
  • Backward compatible - defaults to all tools

📖 See TOOL_CATEGORIES.md for complete guide

New Tools Added

  • Network: NAT Gateways, VPC Endpoints, Internet Gateways, CloudFront, Route53
  • Storage: S3 buckets, storage class recommendations
  • Containers: ECS clusters/services, ECR images, launch templates
  • Messaging: SQS queues, SNS topics, EventBridge rules
  • Database: DynamoDB tables and utilization
  • Monitoring: CloudWatch alarms and dashboards
  • Performance: Lambda cold starts, API Gateway, DynamoDB throttling, RDS insights, CloudFront cache
  • Security: Unencrypted resources, public S3 buckets, permissive security groups
  • Governance: Untagged resources, tag compliance, cost allocation
  • Capacity: ElastiCache, ECS services, Lambda utilization
  • Upgrade: Lambda runtimes, EC2 generations, EBS types, RDS/ElastiCache engines, EKS versions
  • Cost: Savings Plans, Reserved Instances, EBS optimization, snapshots, data transfer, NAT Gateway

📊 Tool Categories

Category Tools Description
🧹 Cleanup 9 Find unused resources to delete
💰 Cost 16 Cost optimization and analysis
📊 Capacity 9 Resource utilization and right-sizing
🔒 Security 5 Security compliance checks
Performance 5 Performance analysis and tuning
🔄 Upgrade 8 Outdated resource detection
🌐 Network 5 Network resource optimization
💾 Storage 2 Storage optimization
📦 Containers 4 Container resource management
💬 Messaging 3 Messaging service cleanup
🗄️ Database 2 Database optimization
📈 Monitoring 3 Monitoring resource cleanup
🚀 Application 2 Application health monitoring
🏛️ Governance 3 Tagging and compliance

Total: 76 tools - Use category filtering to load only what you need!

# Load only cost and cleanup tools (25 tools instead of 76)
export MCP_TOOL_CATEGORIES="cost,cleanup"
python -m aws_finops_mcp

📖 See TOOL_CATEGORIES.md for complete documentation

Features

76 Tools Across 14 Categories - Use category filtering to load only what you need!

🧹 Cleanup Tools (9 tools)

Find unused AWS resources to reduce costs:

  • find_unused_lambda_functions - Lambda functions with no invocations
  • find_unused_elastic_ips - Unattached Elastic IPs ($3.60/month each)
  • find_unused_amis - AMIs not used by instances or ASGs
  • find_unused_load_balancers - Load balancers with no traffic ($22-32/month)
  • find_unused_target_groups - Target groups with no targets or traffic
  • find_unused_log_groups - CloudWatch Log Groups with no recent events
  • find_unused_snapshots - EBS snapshots not associated with AMIs ($0.05/GB/month)
  • find_unused_security_groups - Security groups not attached to resources
  • find_unused_volumes - Unattached EBS volumes

💰 Cost Tools (16 tools)

Cost optimization, analysis, and savings recommendations:

Cost Optimization Hub:

  • get_all_cost_optimization_recommendations - All 19 resource types
  • get_cost_optimization_ec2 - EC2 instance recommendations
  • get_cost_optimization_lambda - Lambda function recommendations
  • get_cost_optimization_rds - RDS instance recommendations
  • get_cost_optimization_ebs - EBS volume recommendations

Cost Explorer:

  • get_cost_by_region - Cost breakdown by AWS region
  • get_cost_by_service - Cost breakdown by AWS service
  • get_cost_by_region_and_service - Combined region and service breakdown
  • get_daily_cost_trend - Daily cost trends with statistics

Savings & Optimization:

  • get_savings_plans_recommendations - Savings Plans recommendations
  • get_reserved_instance_recommendations - RI purchase recommendations
  • analyze_reserved_instance_utilization - RI utilization and coverage
  • get_ebs_volume_type_recommendations - EBS volume type optimization
  • get_snapshot_lifecycle_recommendations - Snapshot lifecycle management
  • analyze_data_transfer_costs - Data transfer cost analysis
  • get_nat_gateway_optimization_recommendations - NAT Gateway optimization

📊 Capacity Tools (9 tools)

Resource utilization analysis for right-sizing:

Compute:

  • find_underutilized_ec2_instances - EC2 with low CPU/memory (≤20%)
  • find_overutilized_ec2_instances - EC2 with high CPU/memory (≥80%)
  • find_underutilized_lambda_functions - Lambda with low invocations

Database:

  • find_underutilized_rds_instances - RDS with low CPU (≤20%)
  • find_overutilized_rds_instances - RDS with high CPU (≥80%)
  • find_underutilized_dynamodb_tables - DynamoDB with low capacity
  • find_overutilized_dynamodb_tables - DynamoDB with high capacity (>80%)
  • find_underutilized_elasticache_clusters - ElastiCache with low CPU (<20%)
  • find_overutilized_elasticache_clusters - ElastiCache with high CPU/memory (>80%)

Containers:

  • find_underutilized_ecs_services - ECS services with low CPU/memory (<20%)

🔒 Security Tools (5 tools)

Security compliance and best practices:

  • find_unencrypted_ebs_volumes - EBS volumes without encryption
  • find_unencrypted_s3_buckets - S3 buckets without default encryption
  • find_unencrypted_rds_instances - RDS instances without encryption
  • find_public_s3_buckets - S3 buckets with public access enabled
  • find_overly_permissive_security_groups - Security groups with 0.0.0.0/0 rules

⚡ Performance Tools (5 tools)

Performance analysis and optimization:

  • analyze_lambda_cold_starts - Lambda cold start analysis
  • analyze_api_gateway_performance - API Gateway performance metrics
  • analyze_dynamodb_throttling - DynamoDB throttling issues
  • analyze_rds_performance_insights - RDS Performance Insights data
  • analyze_cloudfront_cache_hit_ratio - CloudFront cache performance

🔄 Upgrade Tools (8 tools)

Identify outdated resources needing upgrades:

Compute:

  • find_asgs_with_old_amis - Auto Scaling Groups using old AMIs
  • find_outdated_lambda_runtimes - Lambda with deprecated runtimes
  • find_ec2_instances_with_old_generations - EC2 using previous generation types
  • find_ebs_volumes_with_old_types - EBS using previous generation types
  • find_outdated_ecs_platform_versions - ECS not on latest platform version

Database:

  • find_outdated_rds_engine_versions - RDS not on latest engine version
  • find_outdated_elasticache_engine_versions - ElastiCache not on latest version

Containers:

  • find_outdated_eks_cluster_versions - EKS not on latest Kubernetes version

🌐 Network Tools (5 tools)

Network resource optimization:

  • find_unused_nat_gateways - NAT Gateways with no traffic ($32.40/month)
  • find_unused_vpc_endpoints - VPC Endpoints with no connections ($7.20/month per AZ)
  • find_unused_internet_gateways - Unattached Internet Gateways
  • find_unused_cloudfront_distributions - CloudFront with no requests
  • find_unused_route53_hosted_zones - Route53 zones with no queries

💾 Storage Tools (2 tools)

Storage optimization:

  • find_unused_s3_buckets - S3 buckets with no activity
  • get_s3_storage_class_recommendations - S3 storage class optimization (30-95% savings)

📦 Container Tools (4 tools)

Container and orchestration resource management:

  • find_old_ecs_task_definitions - Old ECS task definitions not in use
  • find_unused_ecr_images - Unused ECR images ($0.10/GB/month)
  • find_unused_launch_templates - EC2 launch templates not in use
  • find_unused_ecs_clusters_and_services - ECS clusters/services with no activity

💬 Messaging Tools (3 tools)

Messaging service optimization:

  • find_unused_sqs_queues - SQS queues with no messages
  • find_unused_sns_topics - SNS topics with no subscriptions/messages
  • find_unused_eventbridge_rules - EventBridge rules with no invocations

🗄️ Database Tools (2 tools)

Database resource analysis:

  • find_unused_dynamodb_tables - DynamoDB tables with no read/write activity
  • find_underutilized_dynamodb_tables - DynamoDB with low capacity utilization

📈 Monitoring Tools (3 tools)

Monitoring resource cleanup:

  • find_unused_cloudwatch_alarms - CloudWatch alarms in INSUFFICIENT_DATA state
  • find_orphaned_cloudwatch_dashboards - Dashboards referencing deleted resources
  • find_orphaned_cloudwatch_alarms - Alarms not associated with active resources

🚀 Application Tools (2 tools)

Application health monitoring:

  • find_target_groups_with_high_error_rate - Target groups with 5XX errors (>5%)
  • find_target_groups_with_high_response_time - Target groups with slow response times (>1s)

🏛️ Governance Tools (3 tools)

Resource governance and compliance:

  • find_untagged_resources - Resources missing required tags
  • analyze_tag_compliance - Tag compliance analysis across resources
  • generate_cost_allocation_report - Cost allocation by tags

✨ Tool Features

All tools include:

  • Comprehensive Details - Full ARNs, configurations, and metadata
  • Cost Estimates - Monthly cost savings potential
  • Complete Tags - Cost allocation and ownership tracking
  • Age Calculations - Prioritize cleanup efforts
  • Security Details - Encryption, KMS keys, ownership
  • Total Savings - Aggregate cost savings per tool

🌐 Deployment Modes

Standard Mode (stdio): Direct integration with MCP clients
HTTP Server Mode: Remote access via REST API for distributed deployments

  • Run on EC2 and connect from anywhere
  • SSH tunnel for secure development
  • HTTPS with Nginx for production
  • AWS Systems Manager for no-SSH access
  • API endpoints: /health, /tools, /mcp

Installation

🚀 NEW: Deploy to Amazon Bedrock AgentCore

Deploy this MCP server to AWS Bedrock AgentCore for production-ready, scalable agent integration:

# Quick deployment (recommended)
pip install bedrock-agentcore-starter-toolkit
agentcore launch

Quick Links:

Two Deployment Methods:

  1. Gateway (Lambda) - Quick setup, serverless, cost-effective
  2. Runtime (Container) - Production-ready, unlimited execution time (use agentcore launch)

Quick Start (Virtual Environment)

# Automated setup
./setup.sh

# Run the server (stdio mode)
./run.sh

# Run tests
./test.sh

Manual Installation

# Using pip
pip install .

# Using uv
uv pip install .

# For development
pip install -e ".[dev]"

Docker Installation

Option 1: Standard Mode (stdio)

# Build and run with Docker
./docker-run.sh run

# Or use Docker Compose
docker-compose up -d

# View logs
docker-compose logs -f

Option 2: HTTP Server Mode (Remote Access)

# Run with HTTP server for remote access
docker-compose -f docker-compose-http.yml up -d

# Test the server
curl http://localhost:8000/health

# View logs
docker-compose -f docker-compose-http.yml logs -f

See DEPLOYMENT.md for detailed deployment options including EC2, ECS, Lambda, and Kubernetes.

See REMOTE_ACCESS_GUIDE.md for remote access setup and configuration.

Usage

🎯 Tool Category Filtering (NEW!)

Problem: Loading all 76 tools can be slow and overwhelming for clients.

Solution: Use MCP_TOOL_CATEGORIES to enable only the tools you need!

# Enable only cleanup and cost tools (25 tools instead of 76)
export MCP_TOOL_CATEGORIES="cleanup,cost"
python -m aws_finops_mcp

# Enable all tools (default)
export MCP_TOOL_CATEGORIES="all"
python -m aws_finops_mcp

Available Categories (14 total):

  • cleanup (9 tools) - Find unused resources
  • cost (16 tools) - Cost optimization and analysis
  • capacity (9 tools) - Resource utilization analysis
  • security (5 tools) - Security compliance checks
  • performance (5 tools) - Performance analysis
  • upgrade (8 tools) - Outdated resource detection
  • network (5 tools) - Network resource optimization
  • storage (2 tools) - Storage optimization
  • containers (4 tools) - Container resource management
  • database (2 tools) - Database optimization
  • messaging (3 tools) - Messaging service cleanup
  • monitoring (3 tools) - Monitoring resource cleanup
  • application (2 tools) - Application health monitoring
  • governance (3 tools) - Tagging and compliance

📖 See TOOL_CATEGORIES.md for complete documentation and examples

Mode 1: Standard MCP Server (stdio)

Add to your MCP client configuration (e.g., Kiro's mcp.json):

{
  "mcpServers": {
    "aws-finops": {
      "command": "python",
      "args": ["-m", "aws_finops_mcp"],
      "env": {
        "AWS_PROFILE": "your-profile",
        "AWS_REGION": "us-east-1",
        "MCP_TOOL_CATEGORIES": "cleanup,cost,security"
      }
    }
  }
}

Or using uvx:

{
  "mcpServers": {
    "aws-finops": {
      "command": "uvx",
      "args": ["aws-pillar-mcp-server"]
    }
  }
}

Mode 2: HTTP Server (Remote Access)

Run the server in HTTP mode for remote access:

# Set environment variable
export MCP_SERVER_MODE=http
export MCP_SERVER_HOST=0.0.0.0
export MCP_SERVER_PORT=8000

# Run the server
python -m aws_finops_mcp

# Or use Docker
docker-compose -f docker-compose-http.yml up -d

HTTP API Endpoints

Health Check:

curl http://localhost:8000/health

List Tools:

curl http://localhost:8000/tools

Execute Tool:

curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "get_cost_by_region",
    "arguments": {
      "region_name": "us-east-1"
    }
  }'

Remote Access Options

SSH Tunnel (Recommended for Development):

# On EC2
docker-compose -f docker-compose-http.yml up -d

# On your laptop
ssh -i your-key.pem -L 8000:localhost:8000 ec2-user@your-ec2-ip -N

# Connect to localhost:8000
curl http://localhost:8000/health

HTTPS with Nginx (Recommended for Production):

# Automated setup on EC2
./setup-ec2-remote.sh yes yes your-domain.com

# Access via HTTPS
curl https://your-domain.com/health

See REMOTE_ACCESS_GUIDE.md for complete remote access setup instructions.

Tool Parameters

All tools accept the following parameters:

AWS Credentials (one of):

  • profile_name: AWS profile name
  • role_arn: IAM role ARN to assume
  • access_key + secret_access_key: Direct credentials
  • access_key + secret_access_key + session_token: Temporary credentials

Common Parameters:

  • region_name: AWS region (default: "us-east-1")
  • period: Lookback period in days (default: 90)
  • max_results: Maximum results to return (default: 100)

Example Tool Calls

stdio Mode (MCP Client)

# Find unused Lambda functions
{
  "tool": "find_unused_lambda_functions",
  "arguments": {
    "profile_name": "production",
    "region_name": "us-west-2",
    "period": 90
  }
}

# Find underutilized EC2 instances
{
  "tool": "find_underutilized_ec2_instances",
  "arguments": {
    "role_arn": "arn:aws:iam::123456789012:role/FinOpsRole",
    "region_name": "us-east-1",
    "period": 30
  }
}

# Get cost optimization recommendations
{
  "tool": "get_cost_optimization_ec2",
  "arguments": {
    "access_key": "AKIA...",
    "secret_access_key": "...",
    "region_name": "us-east-1"
  }
}

HTTP Mode (REST API)

# Find unused Lambda functions
curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "find_unused_lambda_functions",
    "arguments": {
      "region_name": "us-west-2",
      "period": 90
    }
  }'

# Get cost by region
curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "get_cost_by_region",
    "arguments": {
      "region_name": "us-east-1"
    }
  }'

# Find underutilized EC2 instances
curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "tool": "find_underutilized_ec2_instances",
    "arguments": {
      "region_name": "us-east-1",
      "period": 30
    }
  }'

AWS Permissions Required

Quick Setup

We provide ready-to-use IAM policies for different use cases:

# Automated setup (recommended)
cd iam-policies/examples
./create-iam-role.sh finops-mcp-role full ec2

# Or create IAM user
./create-iam-user.sh finops-mcp-user full

Available Policies

Policy Use Case Tools Enabled
Full Policy Production (recommended) All 76 tools
Minimal Policy Testing/Development All 76 tools (basic)
Read-Only Policy Maximum security All 76 tools
Cost-Only Policy Cost analysis only 16 cost tools

Policy Files

  • iam-policies/finops-full-policy.json - Complete permissions (recommended)
  • iam-policies/finops-minimal-policy.json - Basic permissions
  • iam-policies/finops-readonly-policy.json - Read-only access
  • iam-policies/finops-cost-only-policy.json - Cost analysis only

Setup Methods

AWS Console: Copy policy JSON → Create Policy → Attach to Role/User

AWS CLI:

aws iam create-policy \
  --policy-name FinOpsFullPolicy \
  --policy-document file://iam-policies/finops-full-policy.json

Terraform: See iam-policies/examples/terraform-example.tf

CloudFormation: See iam-policies/examples/cloudformation-example.yaml

📖 Complete Guide: See IAM_SETUP_GUIDE.md for detailed instructions

Architecture

src/aws_finops_mcp/
├── __main__.py            # Entry point (supports stdio and HTTP modes)
├── server.py              # FastMCP server with all 76 tools
├── server_filtered.py     # Filtered server with category support (NEW!)
├── tool_categories.py     # Category definitions and filtering logic (NEW!)
├── http_server.py         # HTTP server wrapper for remote access
├── session.py             # AWS session management
├── tools/
│   ├── cleanup.py         # Cleanup tools (9 tools)
│   ├── capacity.py        # Capacity analysis tools (4 tools)
│   ├── capacity_compute.py # Compute capacity tools (1 tool)
│   ├── capacity_database.py # Database capacity tools (4 tools)
│   ├── cost.py            # Cost optimization tools (5 tools)
│   ├── cost_explorer.py   # Cost Explorer tools (4 tools)
│   ├── cost_savings.py    # Savings recommendations (3 tools)
│   ├── cost_storage.py    # Storage cost optimization (2 tools)
│   ├── cost_network.py    # Network cost optimization (2 tools)
│   ├── application.py     # Application performance tools (2 tools)
│   ├── upgrade.py         # Upgrade recommendations (1 tool)
│   ├── upgrade_compute.py # Compute upgrade tools (4 tools)
│   ├── upgrade_database.py # Database upgrade tools (2 tools)
│   ├── upgrade_containers.py # Container upgrade tools (1 tool)
│   ├── network.py         # Network optimization tools (5 tools)
│   ├── storage.py         # Storage optimization tools (2 tools)
│   ├── containers.py      # Container management tools (4 tools)
│   ├── messaging.py       # Messaging service tools (3 tools)
│   ├── database.py        # Database optimization tools (2 tools)
│   ├── monitoring.py      # Monitoring resource tools (3 tools)
│   ├── performance.py     # Performance analysis tools (5 tools)
│   ├── security.py        # Security compliance tools (5 tools)
│   └── governance.py      # Governance and tagging tools (3 tools)
└── utils/
    ├── helpers.py         # Helper functions
    └── metrics.py         # CloudWatch metrics utilities

Deployment Modes

stdio Mode (Default):

MCP Client ←→ stdin/stdout ←→ MCP Server ←→ AWS APIs

HTTP Mode (Remote Access):

MCP Client ←→ HTTP/HTTPS ←→ MCP Server ←→ AWS APIs
           (REST API)

Category Filtering (NEW!)

User sets MCP_TOOL_CATEGORIES="cleanup,cost"
         ↓
__main__.py checks environment variable
         ↓
Loads server_filtered.py instead of server.py
         ↓
Only 25 tools registered (cleanup: 9 + cost: 16)
         ↓
Client sees only relevant tools

Development

# Install with dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src/

# Lint
ruff check src/

Environment Variables

Server Configuration

# Server Mode
MCP_SERVER_MODE=http          # Enable HTTP server mode (default: stdio)
MCP_SERVER_HOST=0.0.0.0       # Host to bind to (default: 0.0.0.0)
MCP_SERVER_PORT=8000          # Port to listen on (default: 8000)

# Tool Filtering (NEW!)
MCP_TOOL_CATEGORIES=cleanup,cost  # Enable specific categories (default: all)
                                  # Options: cleanup, cost, capacity, security,
                                  #          performance, upgrade, network, storage,
                                  #          containers, messaging, database,
                                  #          monitoring, application, governance

# AWS Configuration
AWS_REGION=us-east-1          # Default AWS region
AWS_PROFILE=default           # AWS profile name
AWS_ACCESS_KEY_ID=...         # AWS access key (not recommended)
AWS_SECRET_ACCESS_KEY=...     # AWS secret key (not recommended)

# Logging
PYTHONUNBUFFERED=1            # Enable unbuffered output

Example Configurations

stdio Mode with Category Filtering (Recommended):

export MCP_TOOL_CATEGORIES="cleanup,cost,security"
python -m aws_finops_mcp

stdio Mode (All Tools):

python -m aws_finops_mcp

HTTP Mode with Category Filtering:

export MCP_SERVER_MODE=http
export MCP_SERVER_HOST=0.0.0.0
export MCP_SERVER_PORT=8000
export MCP_TOOL_CATEGORIES="cost,capacity"
python -m aws_finops_mcp

Docker HTTP Mode with Filtering:

docker run -e MCP_SERVER_MODE=http \
  -e MCP_SERVER_PORT=8000 \
  -e MCP_TOOL_CATEGORIES="cleanup,cost" \
  -p 8000:8000 \
  aws-pillar-mcp-server

License

MIT License

Quick Reference

Run Modes

Mode Command Use Case
stdio python -m aws_finops_mcp Direct MCP client integration
HTTP MCP_SERVER_MODE=http python -m aws_finops_mcp Remote access, distributed deployments

Docker Commands

# stdio mode
docker-compose up -d

# HTTP mode
docker-compose -f docker-compose-http.yml up -d

# Test HTTP server
curl http://localhost:8000/health

Remote Access

# SSH tunnel (development)
ssh -i key.pem -L 8000:localhost:8000 ec2-user@ec2-ip -N

# HTTPS setup (production)
./setup-ec2-remote.sh yes yes your-domain.com

# Test connection
./examples/test-remote-connection.sh http://localhost:8000

Documentation

Document Description
AGENTCORE_QUICKSTART.md 🆕 Deploy to Amazon Bedrock AgentCore in 5 minutes
BEDROCK_AGENTCORE_DEPLOYMENT.md 🆕 Complete AgentCore deployment guide
AGENTCORE_COMPARISON.md 🆕 Compare Gateway vs Runtime deployment
GETTING_STARTED.md Complete setup guide with MCP configuration
TOOL_CATEGORIES.md Category filtering guide
CATEGORY_QUICK_REFERENCE.md Quick reference for categories
TOOLS_REFERENCE.md All 76 tools documentation
DEPLOYMENT.md Deployment options (EC2, ECS, Lambda, K8s)
REMOTE_ACCESS_GUIDE.md HTTP mode and remote access setup
IAM_SETUP_GUIDE.md IAM permissions and policies
ARCHITECTURE.md System architecture and design
MIGRATION_GUIDE.md Migration guide for category filtering
iam-policies/README.md IAM policy templates

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选