Ikalus1988
Ikalus1988 is an individual open-source developer/creator whose principal project, MisakaNet, is a shared failure-memory protocol for AI coding agents. MisakaNet turns debugging experiences into searchable, evidence-graded lessons so agents and developers do not repeatedly debug the same failures.
At a Glance
- AI coding-agent builders and operators
- Software developers and DevOps engineers
- Users of MCP-compatible coding assistants
- Agent-framework and harness integrators
- +2 more
AI Tools by Ikalus1988
(1)
MisakaNet
Agent Failure Memory Protocol
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Latest News
MisakaNet v2.30.0 released, including a DSH bundle patch fix.
MisakaNet v2.29.0 released with provenance improvements, MCP remote evaluation/E2E work, intake-bot packaging, and additional security/quality automation.
MisakaNet v2.28.0 released during the quality and integration hardening series.
MisakaNet v2.27.0 released as part of the rapid September release cadence.
Products & Services
Open-source, git-backed failure-memory knowledge base and reference implementation for AI coding agents. It stores problem/root-cause/fix/verification lessons as Markdown, supports local zero-dependency BM25 search, and exposes local and hosted MCP interfaces. Apache License 2.0. Sources: https://github.com/Ikalus1988/MisakaNet and https://github.com/Ikalus1988/MisakaNet/blob/main/LICENSE
Hosted HTTP MCP endpoint at https://misakanet.org/mcp with tools for searching lessons, retrieving lessons, submitting intake, writing lessons, preflight, registration, and agent events. The repository describes the hosted implementation as a Cloudflare Worker backed by D1/KV and GitHub issue intake.
Zero-dependency Python BM25 + reciprocal-rank-fusion search engine intended for scripts and notebooks; installed with pip install misakanet-core. Source: https://github.com/Ikalus1988
Zero-dependency Node.js package that captures fatal crashes as tombstone JSON without patching upstream; the homepage presents it as an npm package installable with npx @misaka-net/fatal-guard. Source: https://misakanet.org/
Market Position
MisakaNet positions itself as a public, Git-backed failure/experience knowledge layer rather than a general agent-memory system or skill marketplace. Its stated differentiators are auditable Markdown/version history, zero-dependency local search, evidence levels, intake-to-lesson workflow, and MCP access. The repository explicitly compares it with deadends.dev, Prior, Kira, Casebook-MCP, knownissue, and fix-memory-mcp, while distinguishing general memory products such as Mem0, agentmemory, and Memorix as a different category. Source: https://github.com/Ikalus1988/MisakaNet#how-is-this-different
Leadership
Founders
Ikalus1988
Independent GitHub developer and maintainer who describes their work as building failure-memory MCP servers for AI coding agents. Ikalus1988 is the owner/maintainer of the MisakaNet repository and identifies MisakaNet as the reference implementation's founding node; no prior employer or company is identified in the reviewed sources. (Sources: https://github.com/Ikalus1988 and https://github.com/Ikalus1988/MisakaNet)
Executive Team
Ikalus1988
Creator, maintainer, and founding node
Independent GitHub developer who maintains the MisakaNet reference implementation and describes their focus as failure-memory MCP servers for AI coding agents. Source: https://github.com/Ikalus1988
Founding Story
Ikalus1988's stated premise is that one agent's failure should not become another agent's lesson. MisakaNet was created to make fixes that previously remained in terminal histories into shared, searchable, auditable knowledge: an agent encounters an error, searches lessons for a fix path, and can contribute a redacted failure note when no suitable lesson exists. The initial implementation was designed as zero-dependency, git-backed failure memory, with local BM25 search and later a remote MCP surface. (Source: https://github.com/Ikalus1988/MisakaNet#why)
Business Model
Revenue Model
Open-source and community-operated distribution. The local MCP/CLI is unlimited and free to run; the hosted remote MCP offers anonymous free reads with an IP-based quota and registration for unlimited access. The project says it has spent $0 on bounties and the reviewed sources disclose no paid subscription, license, or usage-revenue program.
Pricing Tiers
Clone the repository or install the Python package; local stdio MCP is described as unlimited.
Hosted MCP access without an account, subject to the documented anonymous read quota.
Registration returns a node ID and token for unlimited remote searches; no paid price is stated.
Target Markets
- AI coding-agent builders and operators
- Software developers and DevOps engineers
- Users of MCP-compatible coding assistants
- Agent-framework and harness integrators
- Researchers evaluating agent recovery, retrieval, and lesson reuse
- Open-source contributors sharing reproducible debugging knowledge
- Recovering from recurring software and infrastructure errors during AI-agent task execution
- Searching known fixes for pip/SSL, Docker, WSL, database, MCP, token, CI, encoding, and RAG failures
- Adding a short failure report when an agent cannot find a suitable existing lesson
- Giving coding agents persistent, cross-project failure memory
- Evaluating whether agents reuse known fixes through retrieval benchmarks
- Using DeepSeek Harness, Claude Code, Cursor, VS Code, Gemini CLI, Windsurf, OpenCode, or Copilot with MCP integrations