Clojurists Together has announced $31K in funding for five Clojure ecosystem projects in Q2 2026, including major work on Malli validation, a Clojure LLM implementation, data analysis tools, a Clojure-to-Go compiler, and an AI protocol implementation. The funding reflects continued investment in improving the Clojure language's capabilities across domains from validation to AI to cross-platform compilation.
Clojurists Together has announced their Q2 2026 funding round, allocating $31,000 USD across five projects that aim to advance various aspects of the Clojure programming language ecosystem. The organization, which relies on member contributions to fund development work in the Clojure community, has selected three major projects to receive $9,000 each and two shorter or experimental projects to receive $2,000 each.
This round of funding continues Clojurists Together's mission of supporting sustainable development of open-source tools in the Clojure ecosystem. The organization has built a model where companies and individual members contribute financially, which is then distributed to developers working on projects that benefit the entire community.
Major Projects ($9K Each)
Malli - Ambrose Bonnaire-Sergeant
Malli is a popular schema validation library for Clojure that has become essential for many applications, including at Metabase, which recently became a Transduce member specifically to support this work. The funding will address a critical optimization challenge that emerged from previous work on recursive schema validation.
In recent improvements to Malli, Bonnaire-Sergeant implemented a change that bounded memory usage during validation of recursive refs, preventing memory leaks in long-running systems when validating large inputs. However, this optimization came with a significant drawback: increased upfront memory usage during validator compilation.
"While they are excited to see validation of nested structures now uses constant memory, the amount of upfront memory required was uncomfortably high," Bonnaire-Sergeant explained regarding Metabase's experience with the optimization.
The project will focus on two potential solutions:
- Discovering recursion points lazily to reduce initial memory use (though this would still allow memory to grow over time)
- Finding ways to reduce maximum memory usage by ensuring references to the same schema point to the same Schema object and validator
This work is particularly important as it addresses a real-world problem faced by production systems using Malli, potentially improving both performance and reliability for Clojure applications.
Uncomplicate AI: Clojure LLM - Dragan Djuric
Dragan Djuric's project aims to create a high-performance local LLM (Large Language Model) solution for Clojure, similar to tools like llama.cpp but with tighter integration into the Clojure ecosystem. The project, which Djuric playfully calls "iLLaManati," will leverage Clojure ONNX Runtime to provide a "batteries included" implementation.
The initial version will focus on Google's Gemma 3 model family, which comes in various sizes from 270M to 27B parameters and supports 140 languages. This choice reflects a pragmatic approach to providing immediate value while maintaining flexibility for future expansion.
What makes this project particularly interesting is its potential to lower the barrier to entry for GPU computing in Clojure. As Djuric explains, "It’s going to be a great low-effort gateway for Clojurists to peek, as users, into high-performance and GPU computing." The library aims to abstract away the complexities of CUDA, ONNX, tensors, and linear algebra, allowing Clojure developers to leverage LLM capabilities without specialized knowledge.
The project represents a significant opportunity for Clojure to establish itself in the rapidly evolving AI space, providing a native solution that doesn't require developers to leave the Clojure ecosystem or learn entirely new paradigms.
SciCloj Documentation and Plotting Libraries - Cvetomir Dimov
SciCloj, a group focused on extending Clojure into data analysis, AI, and scientific computing domains, will use this funding to enhance Noj, the entry point for data analysis in Clojure. The project has three main objectives:
- Extending plotting capabilities by adding more backends and plot types
- Creating a new library for generating interactive dashboards
- Expanding the Noj book for more complete library coverage and consistent structure
This work builds on the success of SciNoj, the first online Clojure conference for data analysis stories, which demonstrated Clojure's suitability for a wide range of applications. By improving the tooling and documentation around data analysis, SciCloj aims to make Clojure more accessible to data scientists and researchers who might otherwise choose more mainstream languages.
The interactive dashboards component is particularly timely, as data visualization and interactive exploration have become essential skills in data analysis workflows. By providing Clojure-native solutions, SciCloj is helping to position Clojure as a viable alternative in domains traditionally dominated by Python and R.
Shorter Projects ($2K Each)
Gloat - Ingy döt Net
Gloat represents an ambitious alternative to GraalVM's native-image for Clojure, promising faster build times, broader platform support, and a completely open-source license. The project already supports compiling Clojure to Go code, native binaries (cross-compiling to approximately 25 targets), Wasm modules, and shared libraries with FFI binding examples in 20+ programming languages.
With this funding, döt Net plans to focus on three key areas:
- Making Gloat/Glojure binaries smaller and faster, with progress already made on "tree shaking" for clojure.core
- Increasing compatibility by passing more of the Clojure Compatibility Test Suite
- Creating tutorial documentation for integration with Go projects and for cross-compilation to various targets
The project's significance lies in its potential to solve a critical pain point for Clojure developers: the complexity and licensing concerns surrounding GraalVM. By providing a viable open-source alternative, Gloat could substantially expand the deployment options for Clojure applications.
PluMCP - Shantanu Kumar
PluMCP is a Clojure implementation of the Model Context Protocol (MCP), which Kumar describes as "a pivotal component of the Agentic AI ecosystem." The project is notable for being the only Clojure+ClojureScript implementation that provides both MCP client and server features, supporting STDIO and Streamable HTTP transports with OAuth2.1 integration.
Currently used by the open-source https://eca.dev project, PluMCP implements version 2025-06-18 of the MCP specification. With this funding, Kumar plans to implement features from the next spec version (2025-11-25) and improve documentation.
Key planned enhancements include:
- Adding OpenID Connect Discovery 1.0 support
- Allowing servers to expose icons as metadata
- Enhancing authorization flows with incremental scope consent
- Validating tool names according to the new spec
- Updating result handling to use more standards-based approaches
- Adding support for URL mode elicitation
This work is particularly relevant as AI agents and tool-using systems become more prevalent. By providing a native Clojure implementation of MCP, PluMCP enables Clojure developers to participate in this emerging ecosystem without leaving their preferred language.
Why This Matters
This round of funding demonstrates several important trends in the Clojure ecosystem:
Maturation of the ecosystem: The diversity of projects—from core libraries like Malli to cutting-edge AI tools—shows Clojure's expanding reach into different domains.
Industry adoption: Companies like Metabase are directly funding work that benefits their operations, indicating Clojure's adoption in production environments.
Bridging communities: Projects like Clojure LLM and Gloat aim to connect Clojure with other ecosystems (AI/ML and Go respectively), expanding Clojure's reach.
Sustainable development model: Clojurists Together's funding mechanism provides a sustainable way to support open-source development without relying solely on corporate sponsorship or developer goodwill.
The funded projects address both immediate practical needs (like Malli's memory optimization) and forward-looking capabilities (like LLM integration), suggesting a balanced approach to ecosystem development. As these projects progress, they're likely to influence the direction of Clojure development and expand its applicability in new domains.
For more information about Clojurists Together and their funding process, visit their official website.

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