CodeSampleX

CodeSampleX

MCP server that helps coding LLMs avoid re-solving common problems by serving verified minimal code samples and compatibility evidence, with tools to search, retrieve, and explain known solutions across languages and environments.

Category
访问服务器

README

CodeSampleX

Stop solving the same code twice.

Languages: English · 한국어 · 日本語 · 简体中文 · Español · Français · Deutsch · Português (BR) · Русский

CodeSampleX is a local-first distributed reasoning cache for coding LLMs. Instead of every agent on Earth re-deriving how a public library works — and re-hitting the same version incompatibilities — CodeSampleX collects anonymous compatibility Evidence from real development environments and serves verified minimal Samples with the exact delta between a known-good answer and your project.

  • Website & Compatibility Explorer: https://codesamplex.dev
  • One question your LLM stops re-answering: does axios.post actually work on axios 1.12 + Node 22 + pnpm + Windows 11 — and if not, at which stage does it break?
  • Works with Claude Code, Codex, Gemini CLI, OpenCode — and any MCP client (Cursor, Windsurf, Cline, Zed, VS Code).

Install

Windows (PowerShell):

irm https://codesamplex.dev/install.ps1 | iex

macOS / Linux:

curl -fsSL https://codesamplex.dev/install.sh | sh

One binary, one question. csx init shows the community contract and asks a single choice — JOIN COMMUNITY or LOCAL ONLY. Everything else (daemon, MCP registration for Claude Code / Codex / Gemini CLI / OpenCode, agent rules) is automatic.

For scripted or CI setups: csx init --community --yes --no-agents does config + identity only and writes nothing outside CSX_HOME; agent config paths otherwise honor CSX_AGENT_HOME when you need them somewhere other than your OS user home.

The contract

You get                              You contribute
✓ Public compatibility knowledge     ✓ Public package/version usage
✓ Verified code answers              ✓ Public API/symbol usage when detectable
✓ Local agent integration            ✓ Build/typecheck/test result
✓ Public sample cache                ✓ Sanitized failure fingerprints

Never shared automatically
✕ Source code        ✕ Repository/project name   ✕ File names or paths
✕ Source snippets    ✕ Secrets or env variables  ✕ Private packages
✕ Raw compiler/runtime logs

This is not hidden telemetry — it is the protocol. Community peers are consumers and producers. Local-only mode never sends anything. The privacy preview in csx ui shows the exact payloads before they leave your machine.

How it works

you build/test through csx (or your agent does)
→ local analysis: public packages, lockfile-resolved versions, symbols, environment
→ raw errors sanitized locally into fingerprints (paths/names/secrets stripped)
→ anonymous evidence batches → Compatibility Graph on codesamplex.dev
→ your LLM asks CSX first: nearest verified Sample + environment delta
→ it reasons about the DELTA, not the whole problem

Four layers, kept honestly separate:

Layer What it is Trust
Evidence Network anonymous package/version/symbol/env/stage/result facts weak→strong, class-labeled
Compatibility Graph aggregated probabilistic map per environment (incl. execution context: Node/Chrome/Safari/Electron/…) derived view
Sample Pool user-approved, clean-room, content-addressed minimal projects contract-verified, cross-verified
Agent Delivery MCP/CLI: nearest sample + delta + known failures graded EXACT→NO_SAFE_MATCH

A project compiling is never presented as a symbol working. Unknown causes stay UNKNOWN. A wrong HIT is worse than a MISS — NO_SAFE_MATCH is a feature.

Agent integration (MCP)

Configured automatically by csx init: Claude Code · Codex · Gemini CLI · OpenCode.

Any other MCP client — Cursor, Windsurf, Cline, Zed, VS Code — works too; csx is a standard stdio MCP server:

{"mcpServers": {"csx": {"command": "csx", "args": ["mcp"]}}}

Model-agnostic: the same compatibility evidence serves Claude, GPT and Codex, Gemini, Llama — any model that can call an MCP tool.

Clients that install MCPB bundles can use codesamplex-mcp.mcpb from the latest release instead. It carries one binary per platform (darwin-arm64, linux-amd64, windows-amd64); on any other architecture use the install script above.

Tools: search_known_solution, get_sample, explain_compatibility, run_observed_command, report_sample_adoption, propose_public_sample, list_local_hits, get_local_stats. Publishing a sample is deliberately not an MCP capability — it requires your explicit CLI approval after a full preview.

csx run -- pnpm build      # observed build → evidence
csx search "axios multipart upload"
csx sample propose --goal "upload a file with axios"
csx ui                     # dashboard + privacy preview

Ecosystems (Public v1)

Node/TypeScript (npm, pnpm, yarn — reference), Python (pip, uv), Go, Rust/Cargo. Honest capability matrix: docs/adapters.md — no adapter claims runtime symbol instrumentation in v1, and symbol resolution confidence is always labeled (EXACT/PROBABLE/UNKNOWN).

Architecture

Single Go binary (csx: daemon + CLI + MCP + peer node + verifier) and a small server (csx-server: PostgreSQL + server-rendered explorer behind Caddy). Samples are content-addressed (sha256) and distributed local-cache-first → peers → main seeder. Downloaded samples never run on your host directly — resolve with --ignore-scripts, compile and contract run network-off in a sandbox, receipts are ed25519-signed. See goal.md (product spec), docs/execution-context.md, docs/operations.md.

Building from source

go build ./cmd/csx && go build ./cmd/csx-server
go test ./...

License

Code: Apache-2.0. Published samples default to MIT-0.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选