--- title: "future-agi vs MiroFish-Offline" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-future-agi-vs-nikmcfly-mirofish-offline" tools: ["future-agi-future-agi", "nikmcfly-mirofish-offline"] --- # future-agi vs MiroFish-Offline *GraphCanon updated Sep 20, 2026* ## Verdict Pick future-agi if future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via,; pick MiroFish-Offline if miroFish-Offline is an offline simulation and prediction engine for multi-agent systems that uses Neo4j and Ollama framework locally. [future-agi](https://futureagi.com) reports 2.0k GitHub stars, 627 forks, and 961 open issues, last pushed Sep 18, 2026. [MiroFish-Offline](https://x.com/nikmcfly69/status/2033147482331390328) has 2.5k stars, 659 forks, and 49 open issues, last pushed Mar 24, 2026. Figures are from public GitHub metadata via [future-agi's repository](https://github.com/future-agi/future-agi) and [MiroFish-Offline's repository](https://github.com/nikmcfly/MiroFish-Offline). | | [future-agi](/tools/future-agi-future-agi.md) | [MiroFish-Offline](/tools/nikmcfly-mirofish-offline.md) | | --- | --- | --- | | Tagline | Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications | Offline multi-agent simulation and prediction engine with Neo4j and Ollama local stack | | Stars | 2,032 | 2,526 | | Forks | 627 | 659 | | Open issues | 961 | 49 | | Language | Python | Python | | Adopt for | Future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via, | MiroFish-Offline is an offline simulation and prediction engine for multi-agent systems that uses Neo4j and Ollama framework locally. | | Persona | - | - | | Runtime | - | - | | License | Apache License 2.0, allowing for free use, modification, and distribution of the software, with the condition that any derivative works also be licensed under the same terms. | AGPL-3.0 | | Categories | AI Agents, Evaluation & Observability, LLM Frameworks | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [future-agi](/tools/future-agi-future-agi.md) | [MiroFish-Offline](/tools/nikmcfly-mirofish-offline.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 179d | | Open issues (now) | 961 | 49 | | Stars delta | +473 (30d) | +58 (30d) | | Open issues delta | +365 (30d) | -1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/future-agi-future-agi/trust.md) | [trust report](/tools/nikmcfly-mirofish-offline/trust.md) | ## Decision facts: future-agi - **Pricing:** freemium - The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing. - **Requirements:** Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment. - **Adopt for:** Future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via, - **License detail:** Apache License 2.0, allowing for free use, modification, and distribution of the software, with the condition that any derivative works also be licensed under the same terms. ## Decision facts: MiroFish-Offline - **Requirements:** Min 16 GB RAM; Requires Docker - **Adopt for:** MiroFish-Offline is an offline simulation and prediction engine for multi-agent systems that uses Neo4j and Ollama framework locally. ## Choose when ### Choose future-agi if… - License: future-agi is Apache-2.0, MiroFish-Offline is AGPL-3.0. - Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing.. - Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment.. - Tags unique to future-agi: ai-agents, ai-evals, ai-gateway, ai-optimization. - Also covers LLM Frameworks. - You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic. ### Choose MiroFish-Offline if… - License: MiroFish-Offline is AGPL-3.0, future-agi is Apache-2.0. - Requirements: Min 16 GB RAM; Requires Docker. - Tags unique to MiroFish-Offline: ai, multi-agent, neo4j, offline. - Use MiroFish-Offline when you require simulations in an offline environment to predict behaviors of multi-agent systems with local data storage options using Neo4j. ## When NOT to use future-agi - You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development. - You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future. - Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source. ## When NOT to use MiroFish-Offline - Avoid MiroFish-Offline if real-time agent interactions are necessary as this tool operates in an offline setup. - Do not use it when your hardware limitations fall below the recommended specifications, such as less than 32 GB RAM and less than 8 cores CPU, especially for efficient LLM inference tasks. ## Common questions ### What is the difference between future-agi and MiroFish-Offline? future-agi: Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. MiroFish-Offline: Offline multi-agent simulation and prediction engine with Neo4j and Ollama local stack. See the comparison table for live GitHub stats and shared categories. ### When should I choose future-agi over MiroFish-Offline? Choose future-agi over MiroFish-Offline when License: future-agi is Apache-2.0, MiroFish-Offline is AGPL-3.0; Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing.; Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment.; Tags unique to future-agi: ai-agents, ai-evals, ai-gateway, ai-optimization; Also covers LLM Frameworks; You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic. ### When should I choose MiroFish-Offline over future-agi? Choose MiroFish-Offline over future-agi when License: MiroFish-Offline is AGPL-3.0, future-agi is Apache-2.0; Requirements: Min 16 GB RAM; Requires Docker; Tags unique to MiroFish-Offline: ai, multi-agent, neo4j, offline; Use MiroFish-Offline when you require simulations in an offline environment to predict behaviors of multi-agent systems with local data storage options using Neo4j. ### When should I avoid future-agi? You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development. You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future. Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source. ### When should I avoid MiroFish-Offline? Avoid MiroFish-Offline if real-time agent interactions are necessary as this tool operates in an offline setup. Do not use it when your hardware limitations fall below the recommended specifications, such as less than 32 GB RAM and less than 8 cores CPU, especially for efficient LLM inference tasks. ### Is future-agi or MiroFish-Offline more popular on GitHub? MiroFish-Offline has more GitHub stars (2,526 vs 2,032). Stars measure visibility, not whether either tool fits your constraints. ### Are future-agi and MiroFish-Offline open source? Yes - both are open-source projects on GitHub (future-agi: Apache-2.0, MiroFish-Offline: AGPL-3.0). ### Where can I find alternatives to future-agi or MiroFish-Offline? GraphCanon lists graph-backed alternatives at [future-agi alternatives](/tools/future-agi-future-agi/alternatives) and [MiroFish-Offline alternatives](/tools/nikmcfly-mirofish-offline/alternatives) ([future-agi markdown twin](/tools/future-agi-future-agi/alternatives.md), [MiroFish-Offline markdown twin](/tools/nikmcfly-mirofish-offline/alternatives.md)), 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](/compare/future-agi-future-agi-vs-nikmcfly-mirofish-offline.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, future-agi or MiroFish-Offline? future-agi: Very active. MiroFish-Offline: Slowing. 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 future-agi and MiroFish-Offline? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [future-agi trust report](/tools/future-agi-future-agi/trust); [MiroFish-Offline trust report](/tools/nikmcfly-mirofish-offline/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-agi-future-agi`](/api/graphcanon/graph?tool=future-agi-future-agi) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_