Comparison
awesome-ai-sdks vs mcpproxy-go
Verdict
Pick awesome-ai-sdks if awesome-ai-sdks offers an extensive directory of SDKs for AI agents, emphasizing its role in managing tools across different languages and ecosystems; pick mcpproxy-go if mcpproxy-go is a proxy server built for developers to enhance AI agents with functionality and security features through the Model Context Protocol (MCP). It supports tool routing, audit logging, and provides a web.
Markdown twin · awesome-ai-sdks alternatives · mcpproxy-go alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | awesome-ai-sdks | mcpproxy-go |
|---|---|---|
| Maintenance | Steady (42d since push) As of 4d · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4d · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No published findings from this source as of 2026-07-11 As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- awesome-ai-sdks
- A database of SDKs for AI agents creation and management
- mcpproxy-go
- Supercharge AI Agents, Safely
Stars
- awesome-ai-sdks
- 1.2k
- mcpproxy-go
- 305
Forks
- awesome-ai-sdks
- 361
- mcpproxy-go
- 43
Open issues
- awesome-ai-sdks
- 241
- mcpproxy-go
- 15
Language
- awesome-ai-sdks
- -
- mcpproxy-go
- Go
Adopt for
- awesome-ai-sdks
- awesome-ai-sdks offers an extensive directory of SDKs for AI agents, emphasizing its role in managing tools across different languages and ecosystems.
- mcpproxy-go
- mcpproxy-go is a proxy server built for developers to enhance AI agents with functionality and security features through the Model Context Protocol (MCP). It supports tool routing, audit logging, and provides a web UI.
Persona
- awesome-ai-sdks
- -
- mcpproxy-go
- -
Runtime
- awesome-ai-sdks
- -
- mcpproxy-go
- -
License
- awesome-ai-sdks
- -
- mcpproxy-go
- MIT
Last pushed
- awesome-ai-sdks
- Jul 9, 2026
- mcpproxy-go
- Aug 2, 2026
Categories
- awesome-ai-sdks
- AI Agents, Developer Tools
- mcpproxy-go
- AI Agents, Developer Tools
Trust and health
Maintenance
- awesome-ai-sdks
- Steady (60%)
- mcpproxy-go
- Very active (96%)
Days since push
- awesome-ai-sdks
- 42d
- mcpproxy-go
- 0d
Open issues (now)
- awesome-ai-sdks
- 241
- mcpproxy-go
- 15
Stars delta
- awesome-ai-sdks
- +6 (30d)
- mcpproxy-go
- Unknown
Open issues delta
- awesome-ai-sdks
- +29 (30d)
- mcpproxy-go
- Unknown
OSV dependency advisories
- awesome-ai-sdks
- No lockfile (source not queried)
- mcpproxy-go
- No published findings from this source as of 2026-07-11
Full report
- awesome-ai-sdks
- Trust report
- mcpproxy-go
- Trust report
Choose awesome-ai-sdks if…
- Tags unique to awesome-ai-sdks: agent, ai-agents, framework, langchain.
- When you are looking to compile and access various SDKs and libraries for AI agent development from one centralized resource.
- More GitHub stars (1.2k vs 305) - visibility, not fit.
When NOT to use awesome-ai-sdks
- For projects requiring a real-time or regularly updated list since the repository acknowledges it's based on their best knowledge and might not be comprehensive.
- If you specifically need production-ready tools. The repository contains links to alpha-stage projects like Chidori, which may not be suitable for immediate deployment.
Choose mcpproxy-go if…
- Pricing: mcpproxy-go is free to use under the MIT license; however, premium support or advanced features may have associated costs..
- Requirements: Min 2 GB RAM; The installation process varies by operating system and includes options for manual setup as well as automated installers for ease of use..
- Tags unique to mcpproxy-go: audit-logging, context-window, local-first, model-context-protocol.
- mcpproxy-go ships Docker support for self-hosted deployment.
- When you need a Go-based solution that focuses specifically on enhancing AI functionalities using MCP.
When NOT to use mcpproxy-go
- When a simpler proxy solution that does not offer specialized AI-focused tools like MCP or advanced logging is sufficient.
- If your project is strictly frontend and does not require backend server enhancement features such as those provided by mcpproxy-go's tool-routing capabilities.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (e2b-dev/awesome-ai-sdks) · observed Aug 21, 2026
- GitHub forks (e2b-dev/awesome-ai-sdks) · observed Aug 21, 2026
- Last push (e2b-dev/awesome-ai-sdks) · observed Jul 9, 2026
- License file (unknown) · observed Aug 21, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (smart-mcp-proxy/mcpproxy-go) · observed Aug 2, 2026
- GitHub forks (smart-mcp-proxy/mcpproxy-go) · observed Aug 2, 2026
- Last push (smart-mcp-proxy/mcpproxy-go) · observed Aug 2, 2026
- License file (MIT) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-ai-sdks 1.2k · mcpproxy-go 305 (synced Aug 21, 2026).
Common questions
- What is the difference between awesome-ai-sdks and mcpproxy-go?
- awesome-ai-sdks: A database of SDKs for AI agents creation and management. mcpproxy-go: Supercharge AI Agents, Safely. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-ai-sdks over mcpproxy-go?
- Choose awesome-ai-sdks over mcpproxy-go when Tags unique to awesome-ai-sdks: agent, ai-agents, framework, langchain; When you are looking to compile and access various SDKs and libraries for AI agent development from one centralized resource; More GitHub stars (1.2k vs 305) - visibility, not fit.
- When should I choose mcpproxy-go over awesome-ai-sdks?
- Choose mcpproxy-go over awesome-ai-sdks when Pricing: mcpproxy-go is free to use under the MIT license; however, premium support or advanced features may have associated costs.; Requirements: Min 2 GB RAM; The installation process varies by operating system and includes options for manual setup as well as automated installers for ease of use.; Tags unique to mcpproxy-go: audit-logging, context-window, local-first, model-context-protocol; mcpproxy-go ships Docker support for self-hosted deployment; When you need a Go-based solution that focuses specifically on enhancing AI functionalities using MCP.
- When should I avoid awesome-ai-sdks?
- For projects requiring a real-time or regularly updated list since the repository acknowledges it's based on their best knowledge and might not be comprehensive. If you specifically need production-ready tools. The repository contains links to alpha-stage projects like Chidori, which may not be suitable for immediate deployment.
- When should I avoid mcpproxy-go?
- When a simpler proxy solution that does not offer specialized AI-focused tools like MCP or advanced logging is sufficient. If your project is strictly frontend and does not require backend server enhancement features such as those provided by mcpproxy-go's tool-routing capabilities.
- Is awesome-ai-sdks or mcpproxy-go more popular on GitHub?
- awesome-ai-sdks has more GitHub stars (1,213 vs 305). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-ai-sdks and mcpproxy-go open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to awesome-ai-sdks or mcpproxy-go?
- GraphCanon lists graph-backed alternatives at awesome-ai-sdks alternatives and mcpproxy-go alternatives (awesome-ai-sdks markdown twin, mcpproxy-go markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, awesome-ai-sdks or mcpproxy-go?
- awesome-ai-sdks: Steady. mcpproxy-go: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for awesome-ai-sdks and mcpproxy-go?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-ai-sdks trust report; mcpproxy-go trust report.