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alex-feel
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context-retrieval-protocol

Retrieve session context from an MCP server using browse-and-retrieve and search patterns.

9|4|Updated Sep 25, 2025
Search Tags:#context#search#mcp#retrieval#semantic#references#hybrid
One-click install
npx skills add https://github.com/alex-feel/mcp-context-server --skill context-retrieval-protocol
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: context-retrieval-protocol
Source: https://github.com/alex-feel/mcp-context-server/tree/main/agents/common/skills/context-retrieval-protocol
Command: npx skills add https://github.com/alex-feel/mcp-context-server --skill context-retrieval-protocol

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides structured patterns and best practices for retrieving and browsing session context from an MCP-compatible context server, enabling consistent discovery and retrieval across agents.

Core Features & Use Cases

  • Browse and Retrieve with separate user and agent searches to build a full context map.
  • Hybrid, semantic, and full-text search patterns to locate relevant context quickly, with guidance on when to use each.
  • References navigation and context continuity to trace decision history and maintain task progress.

Quick Start

Retrieve prior context efficiently by first searching user messages, then agent reports, and finally fetch full content by IDs.

Frequently Asked Questions about context-retrieval-protocol

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I retrieve session context from an MCP server for my AI agent?▼

Session context retrieval from an MCP server uses pattern-based browse-and-retrieve workflows, searching user messages and agent reports first, then fetching full content by IDs to build a complete context map.

When should I use hybrid search versus semantic search for context retrieval?▼

Hybrid search combines keyword and semantic matching for broad context discovery, while semantic search isolates meaning-based relevance, and full-text search targets exact keywords, with guidance provided on when to apply each pattern.

What is the best way to maintain context continuity across multi-agent workflows?▼

Context continuity across multi-agent workflows is maintained by navigating references and tracing decision history through thread-scoped queries, ensuring safe and traceable task progress between agents.

Can I browse and retrieve separate user and agent searches from an MCP context server?▼

Yes, browse-and-retrieve patterns support separate user and agent searches on an MCP context server, enabling agents to systematically discover and fetch relevant session context from both sources independently.

How do I fetch full session content after locating relevant context references?▼

After locating relevant context references through search patterns, you fetch full session content by querying specific context IDs from the MCP server, completing the retrieval workflow efficiently.

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