Calling tools w/ Python improves LLM perf. vs MCP (77.1% on BrowseComp)
If agent's tools are exposed as functions/objects in a Python REPL (as opposed to JSON schemas) they perform better, I linked the explainer article we wrote, but if you want to jump straight in check out the docs! https://docs.symbolica.ai/
Calling tools w/ Python improves LLM perf. vs MCP (77.1% on BrowseComp) launched on December 16, 2025 with 10 votes, #860 of 11,628 launches that month and more than 75% of that year's launches.
In plain words
Symbolica is a Python-based tool framework that improves AI agent performance by exposing tools as native Python functions and objects in a REPL environment rather than JSON schemas. Designed for developers building AI agents, it achieved 77.1% accuracy on the BrowseComp benchmark. The approach allows agents to interact with tools more naturally through Python syntax, potentially making their tool use more efficient and accurate compared to traditional schema-based methods.
written from the facts on this page · September 2026
From the sources
Build agents that interact with runtime objects through code.
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