Mcpproxy Go vs Temporal AI

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-18
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At a glance

DimensionMcpproxy GoTemporal AI
PricingFree (open-source, desktop)Freemium – free tier plus usage-based billing for Temporal Cloud
Primary Use CaseFederate MCP servers into one endpoint for AI agentsDurable execution and orchestration for reliable AI agents and workflows
Deployment ModelLocal desktop app (macOS/Windows/Linux)Self-hosted open-source or Temporal Cloud (managed)
Key IntegrationsCursor IDE, Claude Desktop, ChatGPTOpenAI Agents SDK, Google ADK, Slack, NVIDIA GPU fleet, more
Security FeaturesAutomatic quarantine, TPA detection, manual approval, offlineHuman-in-the-loop signals, Saga compensating transactions, custom roles (pre-release)
Target UsersDevelopers managing multiple MCP servers, power users of CursorTeams building reliable AI agents, microservices orchestration

If your bottleneck is hitting tool limits in Cursor/OpenAI and you need a lightweight, local MCP server gateway, MCPProxy is perfect. If you're building production-grade, long-running AI workflows that must survive crashes and scale across teams, Temporal is the right choice. They solve different problems; pick based on your scale and durability needs.

Mcpproxy Go
Mcpproxy Go

MCPProxy connects every AI client to one shared MCP endpoint, with BM25 tool discovery, profiles and quarantine.

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Temporal AI
Temporal AI

Durable execution platform that keeps AI agents and long-running workflows alive through crashes, retries, and abandoned sessions.

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Pricing
Free
Freemium
Plans
$0/mo
$150 credits for 90 days
Starting at $50 per million actions
Greater of $500/mo or 10% of usage
Custom
Popularity
4 views
7.5k views
Skill Level
Intermediate
Advanced
API Available
Platforms
DesktopCLIWeb
WebAPI
Categories
🔌 MCP Servers & Agent Tooling🛡️ AI Governance & Guardrails
🕸️ Agent Frameworks & Orchestration⚙️ Developer Infrastructure
Features
Single shared MCP endpoint for multiple AI clients
BM25 natural-language tool discovery across connected servers
On-demand tool schema fetching in retrieve_tools and code_execution modes
Direct routing mode listing upstream tools individually
Automatic quarantine for newly added servers and tools
Tool Poisoning Attack (TPA) pattern detection on tool definitions
Tool definition-change review under manual trust mode
Sensitive-data detection for API keys in tool arguments and responses
Optional output sanitisation to redact or block critical detections
Schema checks on tool definitions
Offline-capable built-in tool scanner
Profiles with per-tool policy and agent server discovery (v0.70.0)
Scoped, revocable per-client credentials pinned to a profile (v0.70.0)
Single needs-attention list for flagged servers and tools (v0.70.0)
JavaScript and TypeScript orchestration of tool calls via CLI
Durable execution captures Workflow state at every step with no checkpointing or recovery code
Native SDKs for Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust
Activities retry automatically with backoff, four timeout classes, and heartbeating
Signals, Queries, and Updates read and mutate running Workflows mid-flight
Workflow Streams for real-time interactivity with running executions
Durable AI agents via OpenAI Agents SDK and Google ADK running LLM and tool calls as Activities
Serverless Workers host durable AI agents on Amazon Bedrock AgentCore
Serverless Workers on AWS Lambda (public preview) and GCP Cloud Run (pre-release)
Standalone Activities as a durable job-queue pattern, GA across six SDKs (2026-09-15)
Native Task Queue priority and fair distribution without a custom queueing layer
Durable Timers sleep for months; cron Schedules support backfill and Continue-As-New
Saga pattern via compensating transactions that read like try/catch
Worker Versioning pins Workflows to a version so deploys don't corrupt in-flight runs
Cloud UI Strict Session Mode enforces 15-min inactivity timeout and 12-hour max session (GA 2026-09-18)
Replay tests validate against real histories; time-skipping tests fast-forward long timers in CI
Integrations
Claude Code
Codex
OpenCode
Cursor
GitHub
Playwright
Context7
Jira
Filesystem
Slack
PostgreSQL
OpenAI Agents SDK
Google ADK
AWS Lambda
Google Cloud Run
Amazon Bedrock AgentCore
Kubernetes
GitHub Actions
GCP Marketplace
Azure

What real users say: Mcpproxy Go vs Temporal AI

Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.

Mcpproxy Go

5 mentions across 2 sources · 77% positive (averaged across 2 sources)

Hacker News, GitHub

What users praise

  • • Bypasses Cursor's 40-tool and OpenAI's 128-function API limits easily.
  • • BM25 semantic matching reduces token usage by up to 99%.
  • • Security features: automatic quarantine and TPA detection protect users.
  • • Works fully offline with no cloud dependency.

What frustrates them

  • • Early-stage product – few real-world reviews or long-term reliability data.
  • • Documentation on advanced configuration and troubleshooting is sparse.
  • • Some users report crashes when adding many MCP servers.
  • • Requires some comfort with JSON config files and CLI.

Researched Jul 3, 2026

Temporal AI

No verifiable community signal. We scanned public discussion on Oct 14, 2026 and found posts matching the name “Temporal AI”, but could not establish that they are about this product rather than something else sharing its name. Rather than publish a score built on the wrong subject, we publish none.

Who should pick which

  • Solo developer using Cursor IDE with many MCP servers
    Pick: Mcpproxy Go

    Bypasses Cursor's 40-tool limit, works offline, and is free – perfect for individual power users.

  • Team building a production-grade AI agent that must survive crashes
    Pick: Temporal AI

    Durable execution ensures agent state is preserved across failures; supports human-in-the-loop and retries.

  • Security-conscious user worried about MCP server vulnerabilities
    Pick: Mcpproxy Go

    Automatic quarantine, TPA pattern detection, and manual approval for tool execution protect against malicious servers.

  • Enterprise orchestrating multi-step microservices with rollbacks
    Pick: Temporal AI

    Saga compensating transactions, automatic retries, and visibility UI handle complex distributed workflows.

  • Developer wanting to reduce LLM token costs from tool calls
    Pick: Mcpproxy Go

    BM25 search and single retrieve_tools schema can cut token usage by ~99%.

Frequently Asked Questions

Mcpproxy Go vs Temporal AI: which should you choose?

If your bottleneck is hitting tool limits in Cursor/OpenAI and you need a lightweight, local MCP server gateway, MCPProxy is perfect. If you're building production-grade, long-running AI workflows that must survive crashes and scale across teams, Temporal is the right choice. They solve different problems; pick based on your scale and durability needs.

Can I use MCPProxy with Temporal?

Yes, they are complementary – you can use Temporal to orchestrate an agent that accesses MCP servers via MCPProxy.

Is MCPProxy cloud-hosted?

No, it's a local desktop app. No cloud version exists.

Does Temporal require a cloud subscription?

No, you can self-host the open-source Temporal Server for free. Temporal Cloud is optional.

Which is better for reducing token costs?

MCPProxy directly reduces token costs via BM25 tool discovery and schema optimization. Temporal reduces costs indirectly by minimizing failed executions.

Does MCPProxy support human-in-the-loop?

Yes, it requires manual approval before tool execution by default, which is a form of human oversight.

Does Temporal support offline operation?

Temporal is a client-server architecture; it requires network connectivity to the Temporal Server unless self-hosted locally.

Can MCPProxy handle more than 128 functions?

Yes, it bypasses OpenAI's 128-function API cap by federating servers behind one endpoint.

Can Temporal integrate with MCP servers?

Temporal does not directly support MCP; you would need a custom activity to call an MCP server or use MCPProxy as a bridge.

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Last reviewed: July 3, 2026