Langtail VS Spanly
Langtail VS Spanly对比，Langtail 和 Spanly 有什么区别？
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总结
Langtail 总结
Langtail 着陆页
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
比较详细信息
Langtail 详细信息
| 类别 | 大语言模型 LLMs, AI测试, 无代码与低代码开发, 提示词工程, AI开发者工具, 人工智能接口 |
| Langtail 网站 | https://langtail.com?utm_source=toolify |
| 添加时间 | 2024年4月11日 |
| Langtail 定价 | -- |
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 | -- |
使用情况比较
如何使用 Langtail？
Langtail can be used to test LLM prompts with real-world data, score tests with natural language, pattern matching, or custom code, and experiment with models, parameters, and prompts. It integrates with major LLM providers and offers a TypeScript SDK for developers.
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.
比较 Langtail 和 Spanly 的优势
Langtail的核心功能
- LLM Testing
- AI Firewall
- Prompt Management
- Collaboration Tools
- Data-driven Insights
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
比较使用案例
Langtail的使用案例
- Testing LLM prompts before deployment
- Blocking AI attacks and unsafe outputs
- Managing and refining prompts across teams
- Gaining insights from test results and analytics
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
Langtail和Spanly的不同计划
Langtail
$0 / month + VAT
Unlimited users, 2 prompts or assistants, 1,000 logs per month, 30 days data retention, Public sharebable apps
$99 / month + VAT
1 user, 20 prompts or assistants, Unlimited logs, 90 days data retention, Public sharebable apps
$499 / month + VAT
10 users, Unlimited prompts or assistants, Unlimited logs, 1 year data retention, Public sharebable apps, Radars & Alerts, Dedicated support
Custom
Unlimited users, Unlimited prompts or assistants, Unlimited logs, Custom data retention, Public sharebable apps, Radars & Alerts, AI Firewall, Dedicated support, Self hosting
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.
Langtail的流量
Langtail 是月访问量为 4.7K 且平均访问时长为 00:00:10 的工具。 Langtail 的每次访问页数为 1.77，跳出率为 38.72%。
最新流量情况
| 月访问量 | 4.7K |
| 平均·访问时长 | 00:00:10 |
| 每次访问页数 | 1.77 |
| 跳出率 | 38.72% |
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% |
地理位置
Langtail 的前 5 个国家/地区是：United States 29.90%, India 23.53%, Germany 18.53%, Czech Republic 16.46%, Turkey 11.58%
Top 5 国家/地区
 | 29.90% |
 | 23.53% |
 | 18.53% |
 | 16.46% |
 | 11.58% |
地理位置
对不起，没有数据
流量来源
Langtail 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
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 |
Langtail 或 Spanly哪个更好？
Langtail 可能比 Spanly 更受欢迎。如您所见，Langtail 每月有 4.7K 次访问，而 Spanly 每月有 0 次访问。 所以更多的人选择了Langtail。 因此，人们很可能会在社交平台上更多地推荐 Langtail。
Langtail 的平均访问持续时间为 00:00:10，而 Spanly 的平均访问持续时间为 00:00:00。 此外，Langtail 的每次访问页面为 1.77，跳出率为 38.72%。 Spanly 的每次访问页面为 0.00，跳出率为 0.00%。
Langtail 的主要用户是United States, India, Germany, Czech Republic, Turkey，分布如下：29.90%, 23.53%, 18.53%, 16.46%, 11.58%。
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