- Moved scattered scripts, templates, and documentation into organized directories (applications/, scripts/, assets/). - Updated .gitignore to strictly exclude secrets, state files, and IDE configs. - Added comprehensive README.md outlining repository structure and best practices. - Preserved all existing documentation and technical architecture files. - Prepared infrastructure/ for AWS Org and Proxmox Terraform management.
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1|# 02 - MCP (Model Context Protocol) — Home
2|Purpose: MCP integration guides and implementation examples.
3|
4|## What is MCP?
5|Model Context Protocol (MCP) is a standardized interface for connecting LLMs to external tools, data sources, and services.
6|
7|## MCP Benefits
8|- Unified interface for tool integration
9|- Hot-swappable tool providers
10|- Standardized input/output schemas
11|- Type-safe API definitions
12|
13|## Core Concepts
14|
15|### Tools
16|External capabilities exposed to the model:
17|- File system access
18|- Database queries
19|- API endpoints
20|- Custom business logic
21|
22|### Resources
23|Data sources the model can read:
24|- Documents
25|- Configuration files
26|- Real-time data feeds
27|- Knowledge bases
28|
29|### Prompts
30|Pre-defined interaction templates:
31|- Task initiation patterns
32|- System prompt variations
33|- Role-definition templates
34|
35|## Quick Start
36|
37|bash 38|# Install MCP server 39|pip install mcp-server-filesystem mcp-server-sqlite 40| 41|# Start a filesystem MCP server 42|mcp-server-filesystem --path /path/to/allowed/directory 43| 44|# Connect via client 45|from mcp import ClientSession, StdioServerParameters 46| 47|async with ClientSession( 48| stdio_server_parameters=StdioServerParameters( 49| command="mcp-server-filesystem", 50| args=["--path", "/path/to/allowed/directory"] 51| ) 52|) as session: 53| # List available tools 54| tools = await session.list_tools() 55|
56|
57|## Available MCP Servers
58|
59|- Filesystem: Access documents and configuration files
60|- SQL databases: Query relational databases safely
61|- API Gateway: Connect to REST/GraphQL endpoints
62|- Custom Business Logic: Integrate internal tools and services
63|
64|## Security Considerations
65|
66|- Path whitelisting: Only allow specific directories
67|- Query rate limiting: Prevent resource exhaustion
68|- Input sanitization: Validate all user inputs
69|- Token-based access: Require authentication for sensitive operations
70|
71|## Use Cases
72|
73|- Document analysis: Read and process large document collections
74|- Database queries: Extract insights from operational databases
75|- API orchestration: Coordinate across multiple external services
76|- Code generation: Write and execute code safely
77|
78|## References
79|
80|- MCP Specification
81|- MCP Server Implementations
82|- Integration Examples
83|
84|---
85|
86|MCP integrates seamlessly with OpenClaw agent orchestration for scalable AI applications.
87|