GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
SurfSense is a self-hosted platform offering AI agents that can be used for competitive intelligence research. Here are some critical facts to consider when evaluating it.
Good fit when
- - **Specific Use Cases:** If you need advanced capabilities for competitive intelligence analysis and want the flexibility of connecting various data sources through its connectors, SurfSense might be
Avoid when
- - **Limited Free Tier Capabilities:** Since scraping and crawling are limited only by your hardware when self-hosted without billing enabled, if you have strict limitations on hardware capacity or don
- Pricing:
- unknown - SurfSense is distributed under a license labeled 'Other' which includes no specified pricing. It supports self-hosting with built-in billing off, making scraping and crawling capabilities only limited
- Requirements:
- Requires Docker
Observed Jul 11, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of Aug 18, 2026
- Provenance
- Not a fork · Personal account
- As of Aug 18, 2026
- Security (OSV)
- No criticals
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install SurfSense PyPIHow it fits your stack(7)
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Overview
Self-hosted platform offering AI agents with competitive intelligence capabilities including connectors, automations, and MCP server through Docker-based installation.
Capability facts
- MCP server
- No MCP server detected
Source: repo_scan · Aug 18, 2026
- Languages
- python, javascript
Source: github.language+package.json · Aug 18, 2026
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README
Self host for free Run the entire platform, connectors, agents, automations, and the MCP server on your own infrastructure. Self hosted installs ship with billing off, so scraping, crawling, and agent runs are limited only by your hardware and the model keys you bring. Prerequisi...
For agents
This page has a .md twin and JSON over the API.