
Flowlines
ai.flowlines由 flowlines.ai 發布官方發布者v2.0.0更新於 Oct 29, 2026
MCP observability: analyse MCP server usage, investigate sessions, and instrument MCP servers.
概覽
Flowlines 將助理連接到 Flowlines 工作區,用於 MCP 可觀測性:分析 MCP 伺服器的使用情形、調查工作階段並規劃埋點。
- 可以做什麼
- 檢視 Flowlines 工作區中 MCP 伺服器的使用情形、工具呼叫與使用者活動
- 調查工作階段,了解版本發布後的變化以及工作階段出錯的位置
- 透過 onboarding 工具取得埋點方案,並用 check_onboarding 驗證送達的遙測資料
- 將發現記錄為筆記,並把結果回報到工作區
- 搭配隨附技能進行每週回顧、發布前後比較、工作階段調查、使用者分群建立與資料診斷
- 適用情境
- 適合維運 MCP 伺服器、希望讓助理依據實際使用資料做回顧、比較版本發布、追查失敗工作階段或建立遙測的場合。也適合已將 MCP 或 OTLP 資料送往 Flowlines、想在 Claude Code、Codex 或 ChatGPT 內直接分析的團隊。
- 執行需求
- 需要以 streamable HTTP 連線至 api.flowlines.ai 的遠端 MCP 端點,並完成 OAuth 登入。登入會建立 Flowlines 帳號,工作區與命名空間 API 金鑰在 Flowlines 入門頁面建立。被埋點的伺服器需向 Flowlines 匯出遙測資料。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Flowlines,將其新增到工作區。
- 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
- 為需要使用其工具的對話啟用該服務。
Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。
交給代理程式安裝
把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。
閱讀 https://sourceweft.com/mcp/ai.flowlines%2Fflowlines/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。其他 MCP 客戶端
把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。
{
"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:
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_noteandreport_outcometools. - An MCP server instrumented from the
onboardingplan 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
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
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:
Codex reads a repository-level marketplace from .agents/plugins/marketplace.json:
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:
- Claude Code. In
~/.claude/settings.json, delete these keys fromenv: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, andOTEL_LOG_TOOL_CONTENT. - Codex CLI. In
~/.codex/config.toml, deleteenvironment,log_user_prompt, and theexporterthat containsx-flowlines-api-keyfrom[otel]. Deletehooks = truefrom[features]only if you use no other Codex hooks. In~/.codex/hooks.json, delete theUserPromptSubmit,PostToolUse, andStopentries whose command is"$HOME/.local/lib/flowlines-agent-observability/codex-hook-relay.sh". - Hook relay. Delete
~/.local/lib/flowlines-agent-observability/. - State and backups.
${XDG_CONFIG_HOME:-~/.config}/flowlines-agent-observability/holds copies of your original configuration files inoriginals/, acurl.confthat contains your API key, and aspool/of unsent Codex events that can contain prompt content. If you had your own OpenTelemetry settings before the install, restore them fromoriginals/. Then delete the folder. - 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
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:
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.
- Bump
versioninplugins/flowlines/plugin.json,plugins/flowlines/.claude-plugin/plugin.json,plugins/flowlines/.codex-plugin/plugin.json, and the plugin entry in.claude-plugin/marketplace.json. - Merge to
main. Marketplace installs trackmain; users pick up the new version withclaude plugin update flowlines@flowlinesorcodex plugin marketplace upgrade. - 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:
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
來源:README.md,提交 dc803fe
工具
0版本歷史
1- v2.0.0最新Oct 29, 2026
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