--- title: "lagent vs pi-mcp-adapter" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/internlm-lagent-vs-nicobailon-pi-mcp-adapter" tools: ["internlm-lagent", "nicobailon-pi-mcp-adapter"] --- # lagent vs pi-mcp-adapter *GraphCanon updated Aug 16, 2026* ## Verdict Pick lagent if lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents; pick pi-mcp-adapter if pi-mcp-adapter is a TypeScript-based MCP adapter tailored for efficient token usage with Pi, an AI coding assistant. [lagent](https://github.com/InternLM/lagent) reports 2.3k GitHub stars, 238 forks, and 24 open issues, last pushed Aug 3, 2026. [pi-mcp-adapter](https://github.com/nicobailon/pi-mcp-adapter) has 1.1k stars, 221 forks, and 4 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [lagent's repository](https://github.com/InternLM/lagent) and [pi-mcp-adapter's repository](https://github.com/nicobailon/pi-mcp-adapter). | | [lagent](/tools/internlm-lagent.md) | [pi-mcp-adapter](/tools/nicobailon-pi-mcp-adapter.md) | | --- | --- | --- | | Tagline | A lightweight framework for building LLM-based agents | Token-efficient MCP adapter for Pi coding agent | | Stars | 2,276 | 1,072 | | Forks | 238 | 221 | | Open issues | 24 | 4 | | Language | Python | TypeScript | | Adopt for | lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents. | pi-mcp-adapter is a TypeScript-based MCP adapter tailored for efficient token usage with Pi, an AI coding assistant. | | Persona | - | - | | Runtime | - | - | | License | lagent is open-source under the Apache-2.0 license, allowing for broad use and modification with attribution. | Licensed under MIT | | Categories | AI Agents, LLM Frameworks | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lagent](/tools/internlm-lagent.md) | [pi-mcp-adapter](/tools/nicobailon-pi-mcp-adapter.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 12d | 1d | | Open issues (now) | 24 | 4 | | Stars delta | +8 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/internlm-lagent/trust.md) | [trust report](/tools/nicobailon-pi-mcp-adapter/trust.md) | ## Decision facts: lagent - **Pricing:** freemium - Available freely due to its open-source nature, but customization or enterprise support might involve additional costs. - **Adopt for:** lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents. - **License detail:** lagent is open-source under the Apache-2.0 license, allowing for broad use and modification with attribution. ## Decision facts: pi-mcp-adapter - **Requirements:** pi-mcp-adapter operates in a TypeScript environment and requires that the project already supports TypeScript. - **Adopt for:** pi-mcp-adapter is a TypeScript-based MCP adapter tailored for efficient token usage with Pi, an AI coding assistant. - **License detail:** Licensed under MIT ## Choose when ### Choose lagent if… - lagent is primarily Python; pi-mcp-adapter is TypeScript. - License: lagent is Apache-2.0, pi-mcp-adapter is MIT. - Pricing: Available freely due to its open-source nature, but customization or enterprise support might involve additional costs.. - Tags unique to lagent: agent, gpt, transformers. - Also covers LLM Frameworks. - When you need a streamlined approach to develop LLM-based agents with minimal overhead, lagent can be particularly advantageous due to its lightweight design. ### Choose pi-mcp-adapter if… - pi-mcp-adapter is primarily TypeScript; lagent is Python. - License: pi-mcp-adapter is MIT, lagent is Apache-2.0. - Requirements: pi-mcp-adapter operates in a TypeScript environment and requires that the project already supports TypeScript.. - Tags unique to pi-mcp-adapter: ai, claude, coding-agent, extension. - pi-mcp-adapter ships an MCP server manifest. - Use when working with Pi, the AI coding assistant, to optimize token efficiency within Model Context Protocol environments. ## When NOT to use lagent - Avoid using lagent if your project necessitates integration with a broader set of tools that are not natively supported by this framework, as it offers limited out-of-the-box extensibility. - Steer clear if you need robust scalability features right from the start. While lightweight, lagent may require additional custom work to handle more demanding scaling requirements. ## When NOT to use pi-mcp-adapter - Avoid if your project does not align with TypeScript or the Model Context Protocol framework as pi-mcp-adapter is specifically tailored for these contexts. - Do not use when working on projects that do not involve Pi coding assistant, as its functionalities are directly tied to this specific AI tool. ## Common questions ### What is the difference between lagent and pi-mcp-adapter? lagent: A lightweight framework for building LLM-based agents. pi-mcp-adapter: Token-efficient MCP adapter for Pi coding agent. See the comparison table for live GitHub stats and shared categories. ### When should I choose lagent over pi-mcp-adapter? Choose lagent over pi-mcp-adapter when lagent is primarily Python; pi-mcp-adapter is TypeScript; License: lagent is Apache-2.0, pi-mcp-adapter is MIT; Pricing: Available freely due to its open-source nature, but customization or enterprise support might involve additional costs.; Tags unique to lagent: agent, gpt, transformers; Also covers LLM Frameworks; When you need a streamlined approach to develop LLM-based agents with minimal overhead, lagent can be particularly advantageous due to its lightweight design. ### When should I choose pi-mcp-adapter over lagent? Choose pi-mcp-adapter over lagent when pi-mcp-adapter is primarily TypeScript; lagent is Python; License: pi-mcp-adapter is MIT, lagent is Apache-2.0; Requirements: pi-mcp-adapter operates in a TypeScript environment and requires that the project already supports TypeScript.; Tags unique to pi-mcp-adapter: ai, claude, coding-agent, extension; pi-mcp-adapter ships an MCP server manifest; Use when working with Pi, the AI coding assistant, to optimize token efficiency within Model Context Protocol environments. ### When should I avoid lagent? Avoid using lagent if your project necessitates integration with a broader set of tools that are not natively supported by this framework, as it offers limited out-of-the-box extensibility. Steer clear if you need robust scalability features right from the start. While lightweight, lagent may require additional custom work to handle more demanding scaling requirements. ### When should I avoid pi-mcp-adapter? Avoid if your project does not align with TypeScript or the Model Context Protocol framework as pi-mcp-adapter is specifically tailored for these contexts. Do not use when working on projects that do not involve Pi coding assistant, as its functionalities are directly tied to this specific AI tool. ### Is lagent or pi-mcp-adapter more popular on GitHub? lagent has more GitHub stars (2,276 vs 1,072). Stars measure visibility, not whether either tool fits your constraints. ### Are lagent and pi-mcp-adapter open source? Yes - both are open-source projects on GitHub (lagent: Apache-2.0, pi-mcp-adapter: MIT). ### Where can I find alternatives to lagent or pi-mcp-adapter? GraphCanon lists graph-backed alternatives at [lagent alternatives](/tools/internlm-lagent/alternatives) and [pi-mcp-adapter alternatives](/tools/nicobailon-pi-mcp-adapter/alternatives) ([lagent markdown twin](/tools/internlm-lagent/alternatives.md), [pi-mcp-adapter markdown twin](/tools/nicobailon-pi-mcp-adapter/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/internlm-lagent-vs-nicobailon-pi-mcp-adapter.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lagent or pi-mcp-adapter? lagent: Active. pi-mcp-adapter: Very active. 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 lagent and pi-mcp-adapter? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lagent trust report](/tools/internlm-lagent/trust); [pi-mcp-adapter trust report](/tools/nicobailon-pi-mcp-adapter/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=internlm-lagent`](/api/graphcanon/graph?tool=internlm-lagent) - 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/_