Agentmetry vs AgentPort: Which is Better in 2026?
A comprehensive comparison of Agentmetry and AgentPort covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Agentmetry if:
- →You want more affordable paid plans (from $2/mo)
- →You need records agent activity at the tool boundary or mitre att&ck technique tagging per event
- →Your primary focus is ai security & testing
Choose AgentPort if:
- →You need mcp server and cli entry points for any agent or dozens of built-in connectors including linear, slack, github, notion and stripe
- →Your primary focus is ai agent infrastructure
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Agentmetry vs AgentPort: At a Glance
Pricing Comparison: Agentmetry vs AgentPort
Understanding the pricing differences between Agentmetry and AgentPort is crucial for making the right choice. Here's how their plans compare side by side.
Agentmetry Pricing
💡 Pricing takeaway: Both Agentmetry and AgentPort offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Agentmetry and AgentPort stacks up.
What Makes Each Tool Unique
🔵 Unique to Agentmetry
Features available in Agentmetry but not in AgentPort:
- ✓Records agent activity at the tool boundary
- ✓MITRE ATT&CK technique tagging per event
- ✓Sequence correlation into single critical alerts
- ✓Runs fully local with zero cloud calls
- ✓Secret values excluded from the trail
- ✓SIEM-readable output format
🟣 Unique to AgentPort
Features available in AgentPort but not in Agentmetry:
- ✓MCP server and CLI entry points for any agent
- ✓Dozens of built-in connectors including Linear, Slack, GitHub, Notion and Stripe
- ✓Per-tool allow, deny and human-approval policies
- ✓Advanced rule-based filtering on individual tool calls
- ✓Complete audit logs of every tool call and approval chain
- ✓Open source and self-hostable, with a managed cloud in beta
Use Case Recommendations
Best for: Agentmetry
Agentmetry is a local flight recorder for AI coding agents, written for the security engineer who found out their company was running Cursor by reading a pull request. Endpoint detection sees a process; it does not see that an agent read a private SSH key and then made an outbound network call in the same session. Agentmetry records agent activity at the tool boundary — every read, shell command and fetch — correlates the sequence, tags it against MITRE ATT&CK technique IDs, and raises a single critical alert for the pattern rather than a stream of individually unremarkable events. The worked example on the homepage is exactly that: a `cat ~/.ssh/id_rsa` read tagged T1552.004, an `aws configure list` shell call tagged T1059 with DLP flagging an AWS access key, and a WebFetch to a paste site tagged T1071.001, correlated into one credential-exfil finding. Secret values themselves are never written to the trail. It runs entirely on the machine with zero cloud calls, ships nine detection rules in the current phase, and emits in a format existing SIEMs already read, so it slots into an established pipeline rather than becoming another console. Install is a git clone plus `pip install -e`, with a PowerShell installer for Windows. The whole thing is Apache-2.0 open source with the code public, which matters for a tool whose entire value proposition is that it watches privileged activity.
Ideal use cases:
- •Teams or individuals who need records agent activity at the tool boundary
- •Teams or individuals who need mitre att&ck technique tagging per event
- •Teams or individuals who need sequence correlation into single critical alerts
- •Teams or individuals who need runs fully local with zero cloud calls
- •Anyone focused on security workflows
- •Anyone focused on agents workflows
Best for: AgentPort
AgentPort is an open-source security gateway that sits between AI agents and the tools they call, so an agent's access to production systems is governed by policy rather than by whichever API keys happened to end up in its environment. Agents connect through either an MCP server or a CLI, and from there reach Linear, Slack, GitHub, Notion, Stripe and dozens of other connectors that ship out of the box, plus any additional MCP server or REST API you point it at. The control layer is where the value sits: you define which tools a given agent may call outright, which require a human approval before execution, and — for the more cautious — advanced rule-based filtering that can gate on the shape of the call rather than just its name. Every tool call and every approval chain is written to an audit log, which turns an agent's behaviour from something you infer from outcomes into something you can read after the fact. This is the missing piece in most agent deployments: the agent framework decides what to attempt and the credential decides what is possible, with nothing in between. Deployment is either self-hosted from the open-source repository on your own infrastructure, or a managed cloud service currently in beta. AgentPort is built by Skald Labs, based in San Francisco.
Ideal use cases:
- •Teams or individuals who need mcp server and cli entry points for any agent
- •Teams or individuals who need dozens of built-in connectors including linear, slack, github, notion and stripe
- •Teams or individuals who need per-tool allow, deny and human-approval policies
- •Teams or individuals who need advanced rule-based filtering on individual tool calls
- •Anyone focused on agents workflows
- •Anyone focused on mcp workflows
🛡️ Other AI Security & Testing Tools to Consider
Agentmetry and AgentPort aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
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Frequently Asked Questions
Is Agentmetry better than AgentPort?
It depends on your needs. Agentmetry offers 6 key features including Records agent activity at the tool boundary and MITRE ATT&CK technique tagging per event, while AgentPort provides 6 features including MCP server and CLI entry points for any agent and Dozens of built-in connectors including Linear, Slack, GitHub, Notion and Stripe. Agentmetry uses a open-source model with a free tier, while AgentPort is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is Agentmetry cheaper than AgentPort?
Agentmetry is cheaper, starting at Apache-2.0 open source, installed from GitHub. No paid tier or pricing page is published as of August 2026. compared to AgentPort's $12/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Agentmetry and AgentPort together?
Yes, many users combine Agentmetry and AgentPort in their workflow. Agentmetry excels at records agent activity at the tool boundary, while AgentPort shines with mcp server and cli entry points for any agent. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Agentmetry and AgentPort?
Agentmetry is primarily a ai security & testing tool focused on local, open-source flight recorder that tags ai agent activity with mitre att&ck, while AgentPort focuses on ai agent infrastructure with open-source security gateway for ai agents — granular tool policies, approval chains and full audit logs. They serve different primary use cases despite being alternatives.
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