经 AI Skill Hub 精选评估,MCP工具 获评「强烈推荐」。这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.0 分,适合有一定技术背景的用户使用。
MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/PrinceGabriel-lgtm/freshcontext-mcp
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"mcp--": {
"command": "npx",
"args": ["-y", "freshcontext-mcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 MCP工具 执行以下任务... Claude: [自动调用 MCP工具 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"mcp__": {
"command": "npx",
"args": ["-y", "freshcontext-mcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
I asked Claude to help me find a job. It gave me a list of openings. I applied to three of them. Two didn't exist anymore. One had been closed for two years.
Claude had no idea. It presented everything with the same confidence.
That's the problem freshcontext fixes.
This repository is the integrated FreshContext Core/MCP package. FreshContext is the context judgment layer between retrieval and reasoning. Core is the reusable engine that scores, ranks, explains, and turns candidate context into decision-ready context; MCP is the first live host/interface over that engine.
Live demo: freshcontext-mcp.gimmanuel73.workers.dev/demo — same model, same query, two completely different answers. Only the temporal layer changed.
---
Add to your Claude Desktop config and restart:
Mac: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"freshcontext": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://freshcontext-mcp.gimmanuel73.workers.dev/mcp"]
}
}
}
Restart Claude. Done.
Prefer a guided setup? Visit freshcontext-site.pages.dev — 3 steps, no terminal.
The reference implementation runs on Cloudflare's global edge:
| Endpoint | Method | Purpose |
|---|---|---|
/ | GET | Service info + endpoint list |
/health | GET | Liveness check |
/mcp | POST | MCP JSON-RPC transport |
/demo | GET | Live before/after demo (no auth token required) |
/briefing | GET | Latest stored briefing |
/v1/intel/feed/:profile_id | GET | DAR-scored intelligence feed |
/watched-queries | GET | List all watched queries |
Production: https://freshcontext-mcp.gimmanuel73.workers.dev
---
For Claude Desktop, Codex, npx, global npm, and source-checkout setup, see the concise client setup guide.
The npm run demo:* commands below are source-checkout workflows for contributors and evaluators using a cloned repository. The published npm package is the MCP server/runtime package and does not include repo-only source examples or tests.
From an installed npm package, the supported runtime entrypoints are npm start and the freshcontext-mcp binary. Repo-only scripts such as tests, demos, smoke checks, and trust scans print a source-checkout notice when their source files are not present.
The Apify Actor entrypoint remains available in the source checkout for separate actor packaging, but it is intentionally not part of the published MCP npm runtime package.
The clearest MCP path is evaluate_context.
It accepts candidate context from any retriever, agent, database, local script, note parser, or adapter output:
{
"profile": "academic_research",
"intent": "citation_check",
"signals": [
{
"title": "Example source",
"content": "Candidate context text...",
"source": "https://example.com/source",
"source_type": "arxiv",
"published_at": "2026-05-24T12:00:00.000Z",
"retrieved_at": "2026-05-24T13:00:00.000Z",
"semantic_score": 0.92
}
]
}
FreshContext returns decision-first output:
Structured results also include a readable object for humans:
{
"decision": "cite_as_primary",
"label": "Cite as primary",
"readable": {
"label": "Primary source",
"summary": "This source is strong enough to use as main evidence.",
"why": [
"Strong semantic match and current freshness for arxiv.",
"source profile academic_research uses lenient date policy",
"intent profile citation_check selected"
],
"action": "Use this as main evidence while preserving citation and provenance.",
"warnings": [
"FreshContext judges citation readiness and context usefulness; it does not certify truth."
]
}
}
The readable object translates Core decisions into user-facing language. It does not change ranking, decision labels, utility scoring, or source intake. Utility helps explain usefulness for the current question; it remains explanatory and does not control default decision labels or ranking.
FreshContext does not certify truth. It records why context was used, supported, questioned, refreshed, watched, or excluded before it reaches a model.
evaluate_context does not fetch URLs, crawl, scrape, browse, read folders, or call adapters. It only evaluates candidate context the caller provides.
Current boundary: evaluate_context is part of the npm/local stdio MCP server prepared for 0.4.0. The hosted Cloudflare Worker MCP endpoint was last verified separately at 0.4.0 / 22 tools. The Worker remains a separate deployment surface, so future package interfaces should be re-verified remotely before being claimed live.
The repo ships named reference adapters that demonstrate how different source classes can become FreshContext-compatible. Each adapter keeps its own name because it represents a source boundary; the adapter count is operational proof, not the product headline.
高质量的MCP工具,为AI代理提供实时网络智能
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
AI Skill Hub 点评:MCP工具 的核心功能完整,质量优秀。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | freshcontext-mcp |
| 原始描述 | 开源MCP工具:Timestamped web intelligence for AI agents. MCP server with guaranteed freshness。⭐8 · TypeScript |
| Topics | ai-agentscontextfreshnessllmmcptypescript |
| GitHub | https://github.com/PrinceGabriel-lgtm/freshcontext-mcp |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-05-27 · 更新时间:2026-05-30 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端