Spanly VS Open WebUI
Spanly VS Open WebUI对比，Spanly 和 Open WebUI 有什么区别？
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总结
Spanly 总结
Soon, more agents than humans will use your product via MCP. Spanly gives you full observability on the MCP server you ship: error rates, session traces, latency, client analytics, deploy alerts. Drop-in CLI or SDK. US & EU data residency. Built for SaaS engineering teams shipping MCP in production, alongside the Datadog, Sentry, or New Relic you already run.
Spanly 着陆页
Open WebUI 总结
Open WebUI 着陆页
比较详细信息
Spanly 详细信息
| 类别 | 大语言模型 LLMs, AI监控, AI开发者工具 |
| Spanly 网站 | https://www.spanly.com?utm_source=toolify |
| 添加时间 | 2026年6月30日 |
| Spanly 定价 | -- |
Open WebUI 详细信息
| 类别 | 大语言模型 LLMs, AI聊天机器人, 开源AI模型, AI开发者工具, AI工作流, AI助手 |
| Open WebUI 网站 | https://openwebui.com?utm_source=toolify |
| 添加时间 | 2026年7月17日 |
| Open WebUI 定价 | -- |
使用情况比较
如何使用 Spanly？
To use Spanly, you can integrate it into your MCP server by dropping the open-source SDK into your TypeScript or Python code, wrapping your server binary using the Spanly CLI, or deploying it as a Docker sidecar. Once configured with your API key, it automatically captures and traces all MCP-shaped traffic, allowing you to view analytics, errors, and session traces directly via the web dashboard or from your IDE using Spanly's built-in MCP server.
如何使用 Open WebUI？
Install Open WebUI with pip or Docker, then connect it to a model provider such as Ollama, OpenAI, Anthropic, or any compatible API. After setup, use the web interface to chat with models, browse prompts and tools, run retrieval or search workflows, and customize the experience with Python functions and pipelines. Enterprises can deploy it on-premises, in private cloud, hybrid, or air-gapped environments.
比较 Spanly 和 Open WebUI 的优势
Spanly的核心功能
- Protocol-aware tracing capturing full JSON-RPC payloads (arguments, results, errors)
- Real-time session tracking grouping requests end-to-end
- Comprehensive performance metrics broken down by p50, p95, and p99 durations
- Automated error tracking and grouping across servers and clients
- US & EU regional data residency options with GDPR-friendly architecture
- IDE integration allowing engineers to search traces and triage errors from tools like Claude Code or Cursor
Open WebUI的核心功能
- Self-hosted AI chat interface for local and cloud models
- Connects to Ollama, OpenAI, Anthropic, and compatible APIs
- Python-based extensions, functions, and pipelines
- Built-in tools for RAG, search, retrieval, voice, and vision
- Enterprise controls including SSO, RBAC, audit logs, and data residency
- Community library for prompts, models, tools, and workflows
比较使用案例
Spanly的使用案例
- Monitoring production MCP server error rates and performance bottlenecks
- Debugging failing tool calls by inspecting full payload arguments and response details directly
- Tracking down bad deployments by splitting performance metrics out by server and client versions
- Correlating AI agent interactions and sessions across complex multi-turn tool calling workflows
Open WebUI的使用案例
- Run a private local AI assistant on your own hardware
- Deploy a secure internal AI chat platform for employees
- Share prompts, tools, and workflows across a team
- Build a regulated or air-gapped enterprise AI workspace
- Use one interface to manage both local and cloud LLMs
Spanly和Open WebUI的不同计划
Spanly
$0/mo
100,000 MCP requests included (soft cap with sampling). Includes 30 days data retention, 2 seats, and multi-region ingestion. Designed for teams evaluating Spanly on a single server.
$41/mo
Billed annually at $492. Includes 100,000 MCP requests (overage from $6.00/100k decreasing with volume), 90 days data retention, unlimited seats, up to 10 alert rules, and public dashboards.
$210/mo
Billed annually at $2,520. Includes 100,000 MCP requests (overage from $6.00/100k decreasing with volume), 12 months data retention, unlimited seats, up to 100 alert rules, public dashboards, SAML & OIDC single sign-on, audit logs, and priority support.
$125/mo
Locked for 12 months for the 2026 cohort. Includes 1,000,000 requests, all Business features, a direct Slack Connect channel with the founder, roadmap input, and early access to new features in exchange for a monthly feedback call.
Custom Pricing
For volumes above 30M requests/month. Offers a custom per-request rate below $5.00/100k, dedicated support, and custom retention configurations.
Open WebUI
对不起，没有数据
Spanly的流量
Spanly 是月访问量为 0 且平均访问时长为 00:00:00 的工具。 Spanly 的每次访问页数为 0.00，跳出率为 0.00%。
最新流量情况
| 月访问量 | 0 |
| 平均·访问时长 | 00:00:00 |
| 每次访问页数 | 0.00 |
| 跳出率 | 0.00% |
Open WebUI的流量
Open WebUI 是月访问量为 927.0K 且平均访问时长为 00:02:22 的工具。 Open WebUI 的每次访问页数为 3.37，跳出率为 50.73%。
最新流量情况
| 月访问量 | 927.0K |
| 平均·访问时长 | 00:02:22 |
| 每次访问页数 | 3.37 |
| 跳出率 | 50.73% |
地理位置
对不起，没有数据
地理位置
Open WebUI 的前 5 个国家/地区是：United States 17.62%, China 7.43%, Germany 7.42%, India 5.03%, France 4.28%
Top 5 国家/地区
 | 17.62% |
 | 7.43% |
 | 7.42% |
 | 5.03% |
 | 4.28% |
流量来源
Spanly 的 6 个主要流量来源是：邮件 0, vs_sourcesGenAi 0, 直接访问 0, vs_sourcesAffiliate 0, 外链引荐 0, vs_sourcesDisplayAds 0, vs_sourcesSearchPaid 0, vs_sourcesSocialPaid 0, vs_sourcesSearchOrganic 0, vs_sourcesSocialOrganic 0
邮件 | 0 |
vs_sourcesGenAi | 0 |
直接访问 | 0 |
vs_sourcesAffiliate | 0 |
外链引荐 | 0 |
vs_sourcesDisplayAds | 0 |
vs_sourcesSearchPaid | 0 |
vs_sourcesSocialPaid | 0 |
vs_sourcesSearchOrganic | 0 |
vs_sourcesSocialOrganic | 0 |
流量来源
Open WebUI 的 6 个主要流量来源是：vs_sourcesSearchOrganic 46.11%, 直接访问 35.81%, 外链引荐 11.10%, vs_sourcesGenAi 4.55%, vs_sourcesSocialOrganic 1.81%, 邮件 0.49%, vs_sourcesSearchPaid 0.10%, vs_sourcesDisplayAds 0.03%, vs_sourcesAffiliate 0.00%, vs_sourcesSocialPaid 0.00%
vs_sourcesSearchOrganic | 46.11% |
直接访问 | 35.81% |
外链引荐 | 11.10% |
vs_sourcesGenAi | 4.55% |
vs_sourcesSocialOrganic | 1.81% |
邮件 | 0.49% |
vs_sourcesSearchPaid | 0.10% |
vs_sourcesDisplayAds | 0.03% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesSocialPaid | 0.00% |
Spanly 或 Open WebUI哪个更好？
Open WebUI 可能比 Spanly 更受欢迎。如您所见，Spanly 每月有 0 次访问，而 Open WebUI 每月有 927.0K 次访问。 所以更多的人选择了Open WebUI。 因此，人们很可能会在社交平台上更多地推荐 Open WebUI。
Spanly 的平均访问持续时间为 00:00:00，而 Open WebUI 的平均访问持续时间为 00:02:22。 此外，Spanly 的每次访问页面为 0.00，跳出率为 0.00%。 Open WebUI 的每次访问页面为 3.37，跳出率为 50.73%。
Open WebUI 的主要用户是 United States, China, Germany, India, France，分布如下：17.62%, 7.43%, 7.42%, 5.03%, 4.28%。
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