DeepSeek VS Spanly
DeepSeek VS Spanly 对比，DeepSeek 和 Spanly 有什麼區別？
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總結
DeepSeek 總結
DeepSeek 著陸頁
Spanly 總結
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 著陸頁
比較詳情
DeepSeek 詳細信息
| 類別 | 大型語言模型 LLMs, 開源AI模型, AI API, AI聊天機器人, AI 代碼生成, AI助理, AI翻譯, AI寫作 |
| DeepSeek 網站 | https://www.deepseek.com?utm_source=toolify |
| 添加時間 | 2025年2月7日 |
| DeepSeek 定價 | -- |
Spanly 詳細信息
| 類別 | 大型語言模型 LLMs, AI監控, AI 開發者工具 |
| Spanly 網站 | https://www.spanly.com?utm_source=toolify |
| 添加時間 | 2026年6月30日 |
| Spanly 定價 | -- |
使用對比
如何使用DeepSeek？
To use DeepSeek, you can access their models through the DeepSeek Platform API. You'll need to sign up for an account and obtain API keys. The API documentation provides details on how to make requests and integrate the models into your applications.
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.
比較 DeepSeek 和 Spanly 的優點
DeepSeek 的核心功能
- General large language models (LLM)
- Code generation models
- Mixture of Experts (MoE) models
- API access to models
- Context Caching
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
比較用例
DeepSeek 的用例
- Chatbots and conversational AI
- Code completion and generation
- Reasoning and problem-solving
- Text generation and summarization
- Mathematical problem solving
- Search
- Writing
- Reading
- Translation
Spanly 的用例
- 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
DeepSeek 和 Spanly 之間的計劃不同
DeepSeek
對不起，沒有數據
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.
DeepSeek 的流量
DeepSeek 是月访问量為 373.5M 且平均訪問時長為 00:05:13 的工具。 DeepSeek 的每次訪問頁數為 3.26，跳出率為 38.13%。
最新網站流量
| 月訪問量 | 373.5M |
| 平均訪問時長 | 00:05:13 |
| 每次訪問頁數 | 3.26 |
| 跳出率 | 38.13% |
Spanly 的流量
Spanly 是月访问量為 0 且平均訪問時長為 00:00:00 的工具。 Spanly 的每次訪問頁數為 0.00，跳出率為 0.00%。
最新網站流量
| 月訪問量 | 0 |
| 平均訪問時長 | 00:00:00 |
| 每次訪問頁數 | 0.00 |
| 跳出率 | 0.00% |
地理流量
The top 5 countries/regions for DeepSeek are:China 47.85%, Russia 9.94%, United States 5.66%, Hong Kong, China 3.13%, Brazil 2.95%
Top 5 Countries/regions
 | 47.85% |
 | 9.94% |
 | 5.66% |
 | 3.13% |
 | 2.95% |
地理流量
對不起，沒有數據
網站流量來源
DeepSeek 的 6 個主要流量來源是：直接 76.93%, vs_sourcesSearchOrganic 13.70%, 引薦 3.26%, vs_sourcesSocialOrganic 2.68%, vs_sourcesGenAi 2.61%, 郵件 0.66%, vs_sourcesDisplayAds 0.15%, vs_sourcesSearchPaid 0.00%, vs_sourcesAffiliate 0.00%, vs_sourcesSocialPaid 0.00%
直接 | 76.93% |
vs_sourcesSearchOrganic | 13.70% |
引薦 | 3.26% |
vs_sourcesSocialOrganic | 2.68% |
vs_sourcesGenAi | 2.61% |
郵件 | 0.66% |
vs_sourcesDisplayAds | 0.15% |
vs_sourcesSearchPaid | 0.00% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesSocialPaid | 0.00% |
網站流量來源
Spanly 的 6 個主要流量來源是：郵件 0, vs_sourcesGenAi 0, 直接 0, vs_sourcesAffiliate 0, 引薦 0, vs_sourcesDisplayAds 0, vs_sourcesSearchPaid 0, vs_sourcesSocialPaid 0, vs_sourcesSearchOrganic 0, vs_sourcesSocialOrganic 0
郵件 | 0 |
vs_sourcesGenAi | 0 |
直接 | 0 |
vs_sourcesAffiliate | 0 |
引薦 | 0 |
vs_sourcesDisplayAds | 0 |
vs_sourcesSearchPaid | 0 |
vs_sourcesSocialPaid | 0 |
vs_sourcesSearchOrganic | 0 |
vs_sourcesSocialOrganic | 0 |
DeepSeek 或 Spanly哪個更好？
DeepSeek 可能比 Spanly 更受歡迎。如您所見，DeepSeek 每月有 373.5M 次訪問，而 Spanly 每月有 0 次訪問。 所以更多的人選擇DeepSeek。 因此，人們很可能會在社交平台上更多地推薦 DeepSeek。
DeepSeek 的平均訪問持續時間為 00:05:13，而 Spanly 的平均訪問持續時間為 00:00:00。 此外，DeepSeek 的每次訪問頁面為 3.26，跳出率為 38.13%。 Spanly 的每次訪問頁面為 0.00，跳出率為 0.00%。
DeepSeek 的主要用戶是China, Russia, United States, Hong Kong, China, Brazil，分佈如下：47.85%, 9.94%, 5.66%, 3.13%, 2.95%。
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