Flowlines

ai.flowlines由 flowlines.ai 发布官方发布者v2.0.0更新于 Oct 29, 2026

MCP observability: analyse MCP server usage, investigate sessions, and instrument MCP servers.

已验证Streamable HTTP可网页运行开发者工具安全与监控数据与分析

概览

AI 生成的概览

Flowlines 将助手连接到 Flowlines 工作区,用于 MCP 可观测性:分析 MCP 服务器的使用情况、排查会话并规划埋点。

可以做什么
  • 查看 Flowlines 工作区中 MCP 服务器的使用情况、工具调用与用户活动
  • 排查会话,了解版本发布后的变化以及会话出错的位置
  • 通过 onboarding 工具获取埋点方案,并用 check_onboarding 校验到达的遥测数据
  • 将发现记录为笔记,并把结果回报到工作区
  • 配合随附技能完成每周回顾、发布前后对比、会话调查、用户群构建与数据诊断
适用场景
适合运营 MCP 服务器、希望让助手基于真实使用数据做回顾、比较版本发布、追踪失败会话或搭建遥测的场景。也适合已向 Flowlines 发送 MCP 或 OTLP 数据、希望在 Claude Code、Codex 或 ChatGPT 内直接分析的团队。
运行要求
需要以 streamable HTTP 连接 api.flowlines.ai 的远程 MCP 端点,并完成 OAuth 登录。登录会创建 Flowlines 账户,工作区与命名空间 API 密钥在 Flowlines 入门页面创建。被埋点的服务器需向 Flowlines 导出遥测数据。
安装前请注意
该服务器会读取生产环境的 MCP 会话、工具调用与用户活动,返回内容应视为机密。被埋点的服务器会导出工具参数、客户端可见结果与用户身份元数据,其中可能包含个人数据、客户数据或源代码。save_note 与 report_outcome 会写入你的命名空间。命名空间 API 密钥只显示一次,切勿粘贴到对话中。旧的遥测设置若未手动清除,可能继续发送完整提示与工具内容。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Flowlines,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/ai.flowlines%2Fflowlines/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "mcpServers": {
    "flowlines": {
      "type": "http",
      "url": "https://api.flowlines.ai/mcp"
    }
  }
}

README

Flowlines plugins

Official Flowlines plugins for MCP observability. This repository ships the portable flowlines plugin, marketplaces for Claude Code and Codex, and a Cursor plugin manifest (plugins/flowlines/.cursor-plugin/plugin.json) for cursor.directory:

ComponentWhat it does
flowlines MCP serverConnects your MCP client to your Flowlines workspace at https://api.flowlines.ai/mcp. Inspect how people use your MCP servers, what changed since a release, and where sessions go wrong. Record findings as notes. Its onboarding tool returns an instrumentation plan; check_onboarding checks the telemetry that arrives.
flowlines-weekly-review skillA periodic review over the MCP server: what changed since the last review, signals, outcome movements, and what to pin for next time.
flowlines-release-check skillBefore-and-after comparison of an MCP server release: outcomes, intents, cost, signals, and evidence sessions, with the right denominators.
flowlines-investigate-session skillFrom a signal, a user, or a complaint to the failing turn, with minimal exposure of end-user content.
flowlines-cohort-builder skillSizes a user segment, writes it in the Flowlines cohort rule vocabulary, and compares it against a baseline.
flowlines-doctor skillDiagnoses missing or incomplete data across every source: instrumented MCP servers, LangSmith and Langfuse connectors, and OTLP applications.

Privacy notice

  • The Flowlines MCP server reads production MCP sessions, tool calls, and user activity. Treat everything it returns as confidential; it never writes to your namespace except through the explicit save_note and report_outcome tools.
  • An MCP server instrumented from the onboarding plan exports validated tool arguments, client-visible results, and user identity metadata to Flowlines. That data can contain personal data, customer data, source code, or other sensitive content. You choose what it records on the Flowlines get-started page.

onboarding and check_onboarding are read-only: they return an instrumentation plan and check the calls that arrive. The namespace API key is created on the Flowlines get-started page and shown once there; never paste it into chat.

Install

ChatGPT and Codex public plugin

The public distribution target is one Flowlines plugin with the hosted MCP server and four shared analysis skills in OpenAI's Plugins Directory. This repository prepares its submission; merging changes does not publish it or install it for users. A public listing and installation reuse across products still require review and verification.

See the shared plugin guide for the build and verification steps, and the submission worksheet for listing assets and review cases. The existing desktop marketplace installs below continue to work. Personal ChatGPT accounts can test the server separately through Developer mode while the public submission is being prepared.

Claude Code

sh
claude plugin marketplace add flowlines-ai/plugins && claude plugin install flowlines@flowlines

Then run /mcp inside Claude Code and sign in to flowlines. Skills are available as /flowlines:<skill-name>, for example /flowlines:flowlines-weekly-review or /flowlines:flowlines-doctor. Add --scope project to the install command to enable the plugin for one repository only.

Local desktop testing

Open this repository in the ChatGPT desktop app and restart the app after package changes. In the Plugins Directory, select the Flowlines marketplace and install flowlines. The repo catalog at .agents/plugins/marketplace.json points to plugins/flowlines. Complete the MCP sign-in and test in a new chat. Local marketplace support can vary by surface; this does not publish the plugin.

Codex CLI

sh
codex plugin marketplace add flowlines-ai/plugins && codex plugin add flowlines@flowlines

Then sign in with codex mcp login flowlines, or open /plugins inside Codex. Skills are available as $<skill-name>, for example $flowlines-weekly-review or $flowlines-doctor.

The plugin registers an MCP server named flowlines. If you previously added the server by hand under the same name, remove that entry to avoid a duplicate.

After you sign in

Signing in also creates your Flowlines account. When you have no workspace or API key yet, the Flowlines get-started page creates them, then turns green on your server's first tool call. To instrument your MCP server, ask your MCP client to onboard you to Flowlines: it calls onboarding for your namespace, carries out the plan, and verifies the first calls with check_onboarding.

MCP connection errors

If Flowlines calls repeatedly return Internal error or -32603 without a reconnect prompt, use flowlines-doctor when installed. It checks available client status and relevant local logs before treating the failure as an authentication problem. When OAuth refresh has failed, it uses an available native reconnect action or tells you how to reconnect in your client, then verifies tool access before resuming your request. No access to Flowlines infrastructure or server logs is needed.

Recovery uses the failing client's sign-in flow on Windows, macOS, or Linux. Local CLI sign-in must complete credential storage; hosted connectors use their own connection status. If login succeeds but tool calls still fail, the MCP connection may need to be reloaded. The skill reports the remaining recovery step; it does not restart the app automatically.

The public analysis bundle does not include flowlines-doctor. Its analysis skills use the client's native reconnect action for reported authentication problems and direct unresolved failures to Flowlines support.

Team rollout

Claude Code reads marketplaces and plugins from a repository's .claude/settings.json:

json
{  "extraKnownMarketplaces": {    "flowlines": { "source": { "source": "github", "repo": "flowlines-ai/plugins" } }  },  "enabledPlugins": { "flowlines@flowlines": true }}

Codex reads a repository-level marketplace from .agents/plugins/marketplace.json:

json
{  "name": "my-team",  "interface": { "displayName": "My team" },  "plugins": [    {      "name": "flowlines",      "source": {        "source": "git-subdir",        "url": "https://github.com/flowlines-ai/plugins.git",        "path": "./plugins/flowlines",        "ref": "main"      },      "policy": { "installation": "INSTALLED_BY_DEFAULT", "authentication": "ON_USE" },      "category": "Developer Tools"    }  ]}

Remove the old Claude Code and Codex telemetry

Version 0.2.0 removes the flowlines-agent-observability skill. If you used it, its settings stay on your machine and continue to send full prompts, assistant messages, and tool content to Flowlines. The plugin no longer ships its uninstall.sh, so remove the settings manually:

  1. Claude Code. In ~/.claude/settings.json, delete these keys from env: CLAUDE_CODE_ENABLE_TELEMETRY, CLAUDE_CODE_ENHANCED_TELEMETRY_BETA, OTEL_LOGS_EXPORTER, OTEL_TRACES_EXPORTER, OTEL_METRICS_EXPORTER, OTEL_EXPORTER_OTLP_PROTOCOL, OTEL_EXPORTER_OTLP_ENDPOINT, OTEL_EXPORTER_OTLP_HEADERS, OTEL_LOG_USER_PROMPTS, OTEL_LOG_ASSISTANT_RESPONSES, OTEL_LOG_TOOL_DETAILS, and OTEL_LOG_TOOL_CONTENT.
  2. Codex CLI. In ~/.codex/config.toml, delete environment, log_user_prompt, and the exporter that contains x-flowlines-api-key from [otel]. Delete hooks = true from [features] only if you use no other Codex hooks. In ~/.codex/hooks.json, delete the UserPromptSubmit, PostToolUse, and Stop entries whose command is "$HOME/.local/lib/flowlines-agent-observability/codex-hook-relay.sh".
  3. Hook relay. Delete ~/.local/lib/flowlines-agent-observability/.
  4. State and backups. ${XDG_CONFIG_HOME:-~/.config}/flowlines-agent-observability/ holds copies of your original configuration files in originals/, a curl.conf that contains your API key, and a spool/ of unsent Codex events that can contain prompt content. If you had your own OpenTelemetry settings before the install, restore them from originals/. Then delete the folder.
  5. API key. If you used the key only for this telemetry, revoke it in the Flowlines app under Settings, API keys.

Start new Claude Code and Codex sessions to apply the changes.

Repository layout

.claude-plugin/marketplace.json     Claude Code marketplace.agents/plugins/marketplace.json    Codex marketplaceserver.json                         Official MCP Registry entryplugins/flowlines/  plugin.json                       Portable identity and OpenAI listing metadata  mcp.json                          Portable MCP server (streamable-http)  .claude-plugin/plugin.json        Claude Code manifest  .codex-plugin/plugin.json         Codex compatibility manifest  .mcp.json                         Compatibility MCP server (http)  assets/                           Shared icons  skills/                           Shared skills

The portable package follows OpenAI's packaging guide. Hosts discover skills/ and mcp.json at the plugin root. OpenAI listing fields live under extensions.com.openai.interface in plugin.json. That extension replaces the compatibility overlay; the two are not merged. Keep identity, listing fields, versions, and MCP endpoints in sync with the compatibility files. The tests check these values. Existing clients can still use their original manifests and .mcp.json.

Development

Validate the manifests with the real CLIs, then the skill packages:

sh
scripts/validate_plugins.shpython3 scripts/validate_skills.pypython3 -m unittest discover -s scripts -p 'test_public_submission.py'

validate_plugins.sh needs claude and codex on your PATH. It runs offline: Claude validates the manifests, and Codex installs the public bundle and repo plugin separately in a temporary home. Each install must register exactly one MCP server at https://api.flowlines.ai/mcp. These checks do not complete OAuth or call the server.

To try the plugin from a checkout without installing it, run claude --plugin-dir plugins/flowlines, or add this directory as a local marketplace with codex plugin marketplace add ..

Releasing

Plugin 0.5.0 uses the onboarding and check_onboarding tools from MCP server 2.0.0. Deploy that server version before releasing this plugin. The old onboard tool is retired; the user-invoked MCP prompt named onboard remains available.

  1. Bump version in plugins/flowlines/plugin.json, plugins/flowlines/.claude-plugin/plugin.json, plugins/flowlines/.codex-plugin/plugin.json, and the plugin entry in .claude-plugin/marketplace.json.
  2. Merge to main. Marketplace installs track main; users pick up the new version with claude plugin update flowlines@flowlines or codex plugin marketplace upgrade.
  3. Tag the release with claude plugin tag plugins/flowlines.

Public Plugins Directory releases use the separate submission and publication process. A repository merge or tag does not publish that listing.

MCP Registry

server.json lists the remote MCP server, not the plugin, on the official MCP Registry as ai.flowlines/flowlines. A merge does not publish it. Its version follows the MCP server's serverInfo version, and each publish needs a new version.

The registry verifies the ai.flowlines name with a TXT record on the flowlines.ai apex (v=MCPv1; k=ed25519; p=<public key>). Sign in with the matching private key, then publish with mcp-publisher:

sh
mcp-publisher validatemcp-publisher login dns --domain flowlines.ai --private-key "$(openssl pkey -in key.pem -noout -text | grep -A3 'priv:' | tail -n +2 | tr -d ' :\n')"mcp-publisher publish

History

The skills were moved here from flowlines-ai/mcp-server-observability and flowlines-ai/coding-assistant-observability.

Support

Questions or issues: [email protected], or open an issue in this repository.

License

MIT

来源:README.md,提交 dc803fe

工具

0
该服务器需要登录,因此 SourceWeft 无法在没有账号的情况下读取其工具,也未收录。已连接账号所能看到的内容可能因账号及其权限而异。

版本历史

1
  1. v2.0.0最新Oct 29, 2026

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