context-hub
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@context-hubsearch my context files for the latest API design"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Context Hub MVP
本仓库实现 Context Hub v1.1 的本地优先 MVP:以 JSONL/Markdown 为事实源, SQLite FTS5 为可重建索引,并通过 MCP STDIO 与 Streamable HTTP 暴露最小工具面。
首轮开发和验收只使用仓库内测试生成的合成数据,不导入任何既有记忆或个人资料。
当前代码已经用官方 Python MCP SDK 完成本地真实 STDIO、Streamable HTTP 握手、
tools/list 和 context_get 调用。ChatGPT 使用可访问的 HTTPS MCP URL,而不是直接
启动本地 STDIO 进程;产品侧状态、临时纯合成验收入口和人工确认边界记录在
docs/chatgpt-client-status.md。
快速验证
.\.venv\Scripts\python.exe -m pip install -r requirements.lock
.\.venv\Scripts\python.exe -m pip install -e . --no-deps
pwsh -NoLogo -NoProfile -File .\scripts\run_runbook_smoke.ps1
.\.venv\Scripts\python.exe -X utf8 -m unittest discover -s tests -v
.\.venv\Scripts\python.exe -X utf8 scripts\run_multiproject_acceptance.py --output .context-hub-test-data\multiproject-report.json
.\.venv\Scripts\python.exe -X utf8 scripts\run_acceptance.py --output .context-hub-test-data\acceptance-report.jsonPowerShell 冒烟脚本逐条调用手册公开的 CLI,验证初始化、项目注册、清单、检索、稳定 引用分页、显式写入、诊断、删除派生索引后重建,以及备份后恢复到新目录。它只创建 唯一的合成测试目录,结束后删除该目录并保留忽略的 JSON 报告。
多项目验收会在单个临时目录内生成 3 个彼此隔离的项目,验证固定 Top-3 检索集、
项目与类型过滤、分页哈希、源文件变更/删除、历史版本、无损重建,以及本地真实
STDIO 的 manifest → search → read。脚本不读取现有 Context Hub 数据或既有记忆。
安装、只读启动、显式写入、备份恢复和客户端验收步骤见 RUNBOOK.md。
Pi / DeepSeek 的 1,000,000 token 任务上限、截断、重试与墙钟保护实测见
docs/worker-guard-validation.md。
Tool Schema Changelog
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