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Sudhan30/freshprobe

Sudhan30/freshprobe

Data freshness verification: probe en
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add freshprobe -- npx -y freshprobe
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
2 ★ · Sudhan30/freshprobe · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 2 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 Sudhan30/freshprobe;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

freshprobe

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

Data freshness verification for AI agents.
Stop your agents from acting on stale data.
---
> *"I asked my agent to check flight prices. It gave me options. I booked one. The fare had changed 3 hours ago."*
AI agents routinely act on stale data without knowing it. A financial agent queries cached quotes from 47 minutes ago. A support bot tells a customer their order doesn't exist because the CRM hasn't synced. An RAG pipeline confidently answers with yesterday's docs.
**freshprobe** sits between your agent and the external world. Before the agent acts, it asks: *is this data fresh enough?* The answer is always a deterministic JSON verdict: **FRESH**, **STALE**, or **UNKNOWN**.
Single Go binary. No dependencies. Runs as CLI, MCP server, or HTTP microservice.
Why this matters
| Problem | Cost |
|---------|------|
| E-commerce agent used 6-month-old product data | $5M+ revenue loss |
| Enterprise RAG with overlapping refresh infrastructure | $340K/year wasted |
| AI project failures from data quality issues | 60%+ of failures (Gartner) |
Unlike crashes that trigger alerts, stale data produces **confident, well-formatted, completely wrong responses**. Chain a few of those in a multi-agent pipeline and every component reports green while the output is catastrophically wrong.
Install
**Go install (recommended):**
**Docker:**
**From source:**
**GitHub Releases:** Download pre-built binaries for Linux, macOS, and Windows from Releases.
Quick start
Six verification signals
| Signal | What it checks |
|--------|---------------|
| **HTTP cache headers** | Parses Last-Modified, Cache-Control, Age, ETag, Date, Expires. Computes 0.0 to 1.0 freshness score |
| **Endpoint liveness** | Measures response latency (P50/P95/P99), status codes, body size, degradation patterns |
| **Content fingerprinting** | SHA-256 hashes response bodies across repeated probes to detect stale caches |
| **TLS certificate health** | Certificate validity, days remaining, OCSP stapling status |
| **DNS resolution timing** | DNS lookup latency as infrastructure health signal |
| **Redirect chain analysis** | Tracks 301/302/307/308 hops, detects stale CDN configs |
Three deployment modes
CLI
MCP server (for AI agents)
Add to your AI tool config:
Claude Desktop / Claude Code
Cursor
In .cursor/mcp.json:
VS Code (Copilot)
In .vscode/mcp.json:
This exposes three tools to AI agents:
| Tool | Description |
|------|-------------|
| freshprobe_check | Probe a single endpoint. Returns JSON verdict |
| freshprobe_batch | Probe multiple endpoints concurrently |
| freshprobe_policy | Check an endpoint against a named freshness policy |
HTTP server
Policies (freshness-as-code)
Define freshness thresholds per domain in YAML:
When a probe violates a policy:
Example output:
Prometheus metrics
The HTTP server exposes /metrics with Prometheus-compatible text format:
How it compares
| Feature | freshprobe | Uptime Kuma | Gatus | freshcontext-mcp |
来源
awesome · https://github.com/Sudhan30/freshprobe
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