mcp-use VS Polygres
Compare mcp-use VS Polygres, what is the difference between mcp-use and Polygres?
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Summarize
mcp-use summarize
mcp-use is the open-source devtools and cloud infrastructure to help dev teams quickly build and deploy custom AI agents with MCP servers. Our SDK has over 5,000 GitHub stars, 100k downloads, and is trusted by engineers at NASA, Cisco, NVIDIA, etc...
mcp-use Landing Page
Polygres summarize
Polygres turns Postgres into working memory for AI agents. Retrieve structured rows, connected relationships, semantic matches, and full-text results through one hybrid API. All without a separate vector store, graph database, or sync pipeline. Build grounded agents over the data you already have, with relational, graph, and vector context joined at the source. Use the managed cloud or self-host with our open source components. Polygres is currently free to use, just sign up!
Polygres Landing Page
Compare Details
mcp-use details
| Categories | AI Developer Tools, AI API, AI Agent, Large Language Models (LLMs) |
| mcp-use Website | https://mcp-use.com?utm_source=toolify |
| Added Time | August 14 2025 |
| mcp-use Pricing | -- |
Polygres details
| Categories | AI Developer Tools, AI Agent, AI Knowledge Graph, AI API, AI Search Engine |
| Polygres Website | https://polygres.com?utm_source=toolify |
| Added Time | August 26 2026 |
| Polygres Pricing | -- |
Comparison of usage
How to use mcp-use?
Users can get started by installing the mcp-use SDK via `pip install mcp-use` or `npm install mcp-use`. With the SDK, developers can create AI agents by connecting to MCP servers, using any model provider (e.g., Claude). The platform allows spinning up and aggregating MCP servers through a single endpoint. Users can deploy fully managed MCP servers in the mcp-use cloud, sandbox local VMs, or proxy third-party servers behind the gateway, all managed from a single dashboard. An AI-powered chat interface is also available for instant testing and interaction with MCP agents.
How to use Polygres?
Create a Polygres managed instance or install the open-source components on an existing PostgreSQL database. Connect your schema and use the SDK or retrieval API to submit a natural-language query with options such as graph traversal depth, filters, and token limits. Polygres combines relational, graph, vector, and text results into one ranked, token-ready context block that can be passed directly to an AI agent.
Compare Pros between mcp-use and Polygres
Core features of mcp-use
- Open-source SDK for building custom AI agents
- Cloud infrastructure for deploying and managing MCP servers
- Managed MCP Gateway for routing, authentication, and load balancing
- Registry for discovering community-built MCP servers
- Support for various deployment options (cloud, VM, third-party)
Core features of Polygres
- Unified relational, graph, vector, and full-text retrieval
- Native graph traversal over existing PostgreSQL foreign keys
- Fused hybrid search with dense HNSW, sparse, filtered, and semantic retrieval
- Token-ready context assembly for grounded AI agents
- Shortest-path, neighborhood, relationship, and multi-hop graph queries
- Managed cloud hosting and open-source self-hosting
- PostgreSQL-native data retrieval without a separate vector store or sync pipeline
Compare Use Cases
Use cases for mcp-use
- Building and deploying custom AI agents with ease
- Spinning up and aggregating MCP servers through a single endpoint
- Connecting to remote server pools for AI agent operations
- Creating AI products (e.g., with Claude, ChatGPT) using MCP clients
- Managing all MCP infrastructure from a centralized control plane
Use cases for Polygres
- Build grounded AI agents that retrieve customer records, orders, tickets, and related history
- Investigate failed transactions by combining semantic search with order, payment, and dispute relationships
- Create user-memory systems that retrieve relevant past interactions and connected data
- Query Wikipedia-scale datasets using hybrid indexes and graph relationships
- Provide support agents with ranked, database-backed context
- Develop recommendation and discovery systems using existing PostgreSQL data
Different Plan between mcp-use and Polygres
mcp-use
Sorry, there are no data
Polygres
$0 / forever
Open-source pgGraph and pgVector, runnable on any PostgreSQL instance, with community support.
$16 / month
Managed cloud database hosting with email and community Discord support. Currently free for now.
$256 / month minimum usage
Automated vertical and horizontal scaling, email and community Discord support, private Discord or Slack channel, and support hours from 8:00 AM to 5:00 PM.
$4,096 / month minimum usage
Coming soon. Includes dedicated database infrastructure, custom compliance, high availability, 24/7 support, and dedicated support and uptime SLAs.
mcp-use's traffic
mcp-use is the one with 5.1K monthly visits and 00:01:18 Avg.visit duration. mcp-use has a Page per visit of 2.56 and a bounce rate of 36.84%.
Visit Over Time
| Monthly Visits | 5.1K |
| Avg·visit Duration | 00:01:18 |
| Page per Visit | 2.56 |
| Bounce Rate | 36.84% |
Polygres's traffic
Polygres is the one with 11.6K monthly visits and 00:00:12 Avg.visit duration. Polygres has a Page per visit of 1.40 and a bounce rate of 92.09%.
Visit Over Time
| Monthly Visits | 11.6K |
| Avg·visit Duration | 00:00:12 |
| Page per Visit | 1.40 |
| Bounce Rate | 92.09% |
Geography
The top 3 countries/regions for mcp-use are:Canada 38.97%, United States 38.70%, India 22.33%
Top 3 Countries/regions
 | 38.97% |
 | 38.70% |
 | 22.33% |
Geography
The top 1 countries/regions for Polygres are:United States 100.00%
Top 1 Countries/regions
| 100.00% |
Traffic Sources
The 6 main sources of traffic to mcp-use are:Mail 0, vs_sourcesGenAi 0, Direct 0, vs_sourcesAffiliate 0, Referrals 0, vs_sourcesDisplayAds 0, vs_sourcesSearchPaid 0, vs_sourcesSocialPaid 0, vs_sourcesSearchOrganic 0, vs_sourcesSocialOrganic 0
Mail | 0 |
vs_sourcesGenAi | 0 |
Direct | 0 |
vs_sourcesAffiliate | 0 |
Referrals | 0 |
vs_sourcesDisplayAds | 0 |
vs_sourcesSearchPaid | 0 |
vs_sourcesSocialPaid | 0 |
vs_sourcesSearchOrganic | 0 |
vs_sourcesSocialOrganic | 0 |
Traffic Sources
The 6 main sources of traffic to Polygres are:Direct 57.14%, vs_sourcesSocialOrganic 21.37%, vs_sourcesSearchOrganic 13.47%, Referrals 5.27%, Mail 2.75%, vs_sourcesGenAi 0.00%, vs_sourcesAffiliate 0.00%, vs_sourcesDisplayAds 0.00%, vs_sourcesSearchPaid 0.00%, vs_sourcesSocialPaid 0.00%
Direct | 57.14% |
vs_sourcesSocialOrganic | 21.37% |
vs_sourcesSearchOrganic | 13.47% |
Referrals | 5.27% |
Mail | 2.75% |
vs_sourcesGenAi | 0.00% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesDisplayAds | 0.00% |
vs_sourcesSearchPaid | 0.00% |
vs_sourcesSocialPaid | 0.00% |
Which is better: mcp-use or Polygres?
Polygres might be a bit more popular than mcp-use.As you can see, mcp-use has 5.1K monthly visits, while Polygres has 11.6K monthly visits. So more people choose Polygres. So the odds are that people will recommend Polygres more on social platforms.
mcp-use has an Avg.visit duration of 00:01:18, while Polygres has an Avg.visit duration of 00:00:12. Also, mcp-use has a page per visit of 2.56 and a Bounce Rate of 36.84%. Polygres has a page per visit of 1.40 and a Bounce Rate of 92.09%.
The main users of mcp-use are Canada, United States, India, with the following distribution: 38.97%, 38.70%, 22.33%.
The main users of Polygres are United States, with the following distribution: 100.00%.
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