Comparison
AgentsMesh vs mcpproxy-go
Verdict
Pick AgentsMesh if agentsMesh is an AI Agent Workforce Platform with tools for managing multiple local coding agents across various machines via a central console; 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.
Markdown twin · AgentsMesh alternatives · mcpproxy-go alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | AgentsMesh | mcpproxy-go |
|---|---|---|
| Maintenance | Very active (1d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | Published findings 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
- AgentsMesh
- AI Agent Workforce Platform for managing multiple AI coding agents
- mcpproxy-go
- Supercharge AI Agents, Safely
Stars
- AgentsMesh
- 2.3k
- mcpproxy-go
- 305
Forks
- AgentsMesh
- 235
- mcpproxy-go
- 43
Open issues
- AgentsMesh
- 19
- mcpproxy-go
- 15
Language
- AgentsMesh
- Go
- mcpproxy-go
- Go
Adopt for
- AgentsMesh
- AgentsMesh is an AI Agent Workforce Platform with tools for managing multiple local coding agents across various machines via a central console.
- 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
- AgentsMesh
- -
- mcpproxy-go
- -
Runtime
- AgentsMesh
- -
- mcpproxy-go
- -
License
- AgentsMesh
- Other
- mcpproxy-go
- MIT
Last pushed
- AgentsMesh
- Aug 1, 2026
- mcpproxy-go
- Aug 2, 2026
Categories
- AgentsMesh
- AI Agents, Developer Tools
- mcpproxy-go
- AI Agents, Developer Tools
Trust and health
Days since push
- AgentsMesh
- 1d
- mcpproxy-go
- 0d
Open issues (now)
- AgentsMesh
- 19
- mcpproxy-go
- 15
OSV dependency advisories
- AgentsMesh
- Published findings
- mcpproxy-go
- No published findings from this source as of 2026-07-11
Full report
- AgentsMesh
- Trust report
- mcpproxy-go
- Trust report
Choose AgentsMesh if…
- License: AgentsMesh is Other, mcpproxy-go is MIT.
- Tags unique to AgentsMesh: agent-orchestration, ai-agent-workforce-platform, self-hosted.
- When you need to manage and orchestrate numerous AI coding agents locally on your infrastructure
When NOT to use AgentsMesh
- If you do not require the management of multiple, distributed AI coding agents
- When you prefer a managed service without self-hosting responsibilities, as AgentsMesh requires setting up infrastructure manually
Choose mcpproxy-go if…
- License: mcpproxy-go is MIT, AgentsMesh is Other.
- 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 (AgentsMesh/AgentsMesh) · observed Aug 2, 2026
- GitHub forks (AgentsMesh/AgentsMesh) · observed Aug 2, 2026
- Last push (AgentsMesh/AgentsMesh) · observed Aug 1, 2026
- License file (Other) · observed Aug 2, 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: AgentsMesh 2.3k · mcpproxy-go 305 (synced Aug 2, 2026).
Common questions
- What is the difference between AgentsMesh and mcpproxy-go?
- AgentsMesh: AI Agent Workforce Platform for managing multiple AI coding agents. mcpproxy-go: Supercharge AI Agents, Safely. See the comparison table for live GitHub stats and shared categories.
- When should I choose AgentsMesh over mcpproxy-go?
- Choose AgentsMesh over mcpproxy-go when License: AgentsMesh is Other, mcpproxy-go is MIT; Tags unique to AgentsMesh: agent-orchestration, ai-agent-workforce-platform, self-hosted; When you need to manage and orchestrate numerous AI coding agents locally on your infrastructure.
- When should I choose mcpproxy-go over AgentsMesh?
- Choose mcpproxy-go over AgentsMesh when License: mcpproxy-go is MIT, AgentsMesh is Other; 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 AgentsMesh?
- If you do not require the management of multiple, distributed AI coding agents When you prefer a managed service without self-hosting responsibilities, as AgentsMesh requires setting up infrastructure manually
- 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 AgentsMesh or mcpproxy-go more popular on GitHub?
- AgentsMesh has more GitHub stars (2,304 vs 305). Stars measure visibility, not whether either tool fits your constraints.
- Are AgentsMesh and mcpproxy-go open source?
- Yes - both are open-source projects on GitHub (AgentsMesh: Other, mcpproxy-go: MIT).
- Where can I find alternatives to AgentsMesh or mcpproxy-go?
- GraphCanon lists graph-backed alternatives at AgentsMesh alternatives and mcpproxy-go alternatives (AgentsMesh 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, AgentsMesh or mcpproxy-go?
- AgentsMesh: Very active. 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 AgentsMesh and mcpproxy-go?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AgentsMesh trust report; mcpproxy-go trust report.