Custos — The bouncer for your AI agents vs The new Firecrawl /search
Comprehensive feature analysis, ratings breakdown, platform compatibility, and community review comparison.
Custos — The bouncer for your AI agents
Stop AI agents from doing things they shouldn't.
Detailed Feature Comparison Matrix
Compare Other Tools| Dimension | Custos — The bouncer for your AI agents |  The new Firecrawl /search |
|---|---|---|
| Primary Category | Developer Tools | Developer Tools |
| Community Rating | No ratings(0 reviews) | 5.0(15 reviews) |
| Community Upvotes | 7 votes | 268 votes |
| Supported Platforms | Web | Web |
| Tags & Focus | #Artificial Intelligence#Developer Tools#GitHub#Security | #Developer Tools#Search |
| Maker / Company | Independent Developer | Independent Developer |
| Platform Verification | Community Listing | Community Listing |
About Custos — The bouncer for your AI agents
Custos is an open-source safety and control layer designed specifically for AI agents, acting as a reliable 'bouncer' for your applications. As AI agents increasingly interact with critical infrastructure, Custos sits directly between the agent and its tools—such as APIs, files, databases, shell commands, and MCP servers—to intercept and verify every single action before it is executed.
Built for teams deploying AI agents in real-world environments, Custos allows you to explicitly define rule sets determining what an agent is allowed to do, automatically blocking anything outside of those bounds. Furthermore, every action attempted or performed is recorded in a secure, tamper-evident audit trail. With native support for both Python and TypeScript, Custos provides developers with the robust security infrastructure needed to prevent AI agents from performing unintended or harmful actions.
Pros of Custos — The bouncer for your AI agents
- Acts as an interception layer between AI agents and critical tools like APIs, files, databases, shell commands, and MCP servers.
- Provides a tamper-evident audit trail recording every agent action.
- Open-source software built for teams running real-world AI agent environments.
- Supports both Python and TypeScript development stacks.
Cons of Custos — The bouncer for your AI agents
- Relies entirely on developer-defined rules to catch unexpected agent behaviors.
- Limited to Python and TypeScript language support based on current specifications.
- Requires integration work to sit between existing agents and their target tools.
Frequently Asked Questions
What is Custos?
Custos is an open-source safety and control layer for AI agents that sits between the agent and its tools to check every action before it runs, blocking anything outside of defined rules.
Which programming languages are supported?
Custos works with both Python and TypeScript.
How does Custos handle security and tracking?
Custos checks actions against your defined rules and records every action in a tamper-evident audit trail.
What tools can Custos monitor and control?
Custos can monitor actions directed at APIs, files, databases, shell commands, and MCP servers.
About The new Firecrawl /search
The new Firecrawl /search is a specialized Search API built specifically to help AI agents ground themselves in the web efficiently and accurately. Traditionally, enabling AI agents to read full pages for every query burns through context windows and tokens rapidly. Firecrawl solves this by training a custom model that extracts only the specific excerpts from each search result that best answer the user's query.
By providing highly relevant context without the bloat, the tool outperforms processing full pages while using 10x fewer tokens. Notably, on SimpleQA benchmarks, AI agents utilizing Firecrawl /search achieve an impressive score of 94.7%, outperforming competing providers. This feature is live today on every /search call for developers building advanced AI systems.
Pros of The new Firecrawl /search
- Uses 10x fewer tokens compared to processing full web pages
- Delivers highly relevant context and excerpts tailored to specific queries
- Achieves a top-tier 94.7% score on SimpleQA benchmarks for AI agents
- Seamlessly integrated into every /search call
Cons of The new Firecrawl /search
- Primarily optimized for AI agents and developer workflows rather than casual human browsing
- Relies entirely on search-and-excerpt models which may require full-page scraping for edge cases not covered by highlights
Frequently Asked Questions
What is The new Firecrawl /search?
It is a specialized Search API designed for AI agents. Instead of returning full pages that consume tokens quickly, it uses a trained model to return precise excerpts that best answer a given query.
How does Firecrawl /search save tokens?
It uses 10x fewer tokens than traditional methods by extracting only the most relevant content and context excerpts from each search result rather than forcing your AI agent to read full web pages.
How well does it perform on benchmarks?
On SimpleQA, AI agents utilizing Firecrawl /search score 94.7%, which ranks higher than any other competing provider.