EvoKernel MCP sunucusu
Commit 14 Kas 2026Yapay zeka kodlama ajanlarına, token maliyetlerini düşürmek ve tekrarlayan hataları önlemek için AST doğrulamalı bilişsel bellek ve deterministik bir meta-gateway sağlar.
Ayrıca bilinen adı damonless/EvoKernel, evo-kernel
- Yıldızlar
- 3
- Araçlar
- 5
- İndirmeler, 30 gün
- —
- En son sürüm
- —
- Son commit
- 14 Kas 2026
- Lisans
- MIT
EvoKernel MCP nedir?
EvoKernel bir MCP sunucusudur. Yapay zeka kodlama ajanlarına, token maliyetlerini düşürmek ve tekrarlayan hataları önlemek için AST doğrulamalı bilişsel bellek ve deterministik bir meta-gateway sağlar. 5 araç sunar; örneğin evo_search, evo_inspect, evo_run.
Özet, projenin README dosyasından oluşturuldu
EvoKernel MCP sunucusu hakkında
EvoKernel, tekrarlayan hataları önlemek ve token maliyetlerini düşürmek için yapay zeka kodlama ajanlarına AST doğrulamalı bilişsel bellek ve deterministik bir meta-gateway sunar. Claude Code, Cursor, Windsurf, Cline ve GitHub Copilot gibi araçları kullanan geliştiriciler için tasarlanmıştır. Karmaşık MCP araç şemalarını ve monolitik kural dosyalarını beş sabit meta-primitive yapısına indirgeyerek, oturum başlangıcındaki token yükünü önemli ölçüde azaltır ve %100 KV cache hit oranı sağlar.
Sistem, sıfır harici bağımlılık veya dış ağ isteği ile yerel olarak çalışarak gizlilik sağlar ve tedarik zinciri riskini ortadan kaldırır. Kullanıcılar; ana bilgisayar kurallarını taramak, IDE'leri gizli modda bağlamak veya AST belleklerini ve geri çağırma geçmişini incelemek için EvoKernel Workbench'i başlatmak amacıyla npx komutlarını kullanarak ortamı başlatabilirler. Bağlamı; kuralları, SKILL'leri ve bellekleri içeren yerel bir .evo dizini aracılığıyla yönetir; bu da ekiplerin cache dosyalarını gizli tutarken hata düzeltmelerini Git üzerinden paylaşmasına olanak tanır.
Neler yapabilirsiniz
- 1Tekrarlayan kodlama hatalarını önlemeBir yapay zeka ajanı, bir hata bir kez düzeltildiğinde farklı kodlama oturumları boyunca düzeltilmiş kalmasını sağlamak için AST doğrulamalı belleği kullanabilir.
- 2LLM API giderlerini azaltmaGeliştiriciler, araç şemalarını sıkıştırmak için meta-gateway kullanarak toplam token yükünü ve API maliyetlerini düşürebilirler.
- 3Proje zekasını ekiplerle paylaşmaEkipler, doğrulanmış belleği ve araç dizinlerini bir depoya (repository) commit ederek her üyenin paylaşılan kök neden düzeltmelerinden yararlanmasını sağlayabilir.
- 4Ajan yeteneklerini ve belleğini denetlemeÇok dallı (multi-branch) AST belleğinin güncelliğini ve canlı MCP el sıkışmalarını incelemek için görsel workbench'i kullanabilirsiniz.
Projenin README dosyasından alınmıştır. Her kullanım durumu, oradaki bir alıntı ile kontrol edilir.
EvoKernel MCP nasıl yüklenir
Biçimler 10 Kas 2026 tarihinde doğrulandıCursor'a ekleGoose'a ekleEvoKernel MCP'yi Claude Code içine yükleyin
$ claude mcp add evokernel -- npx -y evo-kernelEvoKernel MCP'yi Cursor içine yükleyin
~/.cursor/mcp.json
{
"mcpServers": {
"evokernel": {
"command": "npx",
"args": [
"-y",
"evo-kernel"
]
}
}
}EvoKernel MCP'yi VS Code içine yükleyin
.vscode/mcp.json
{
"servers": {
"evokernel": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"evo-kernel"
]
}
}
}EvoKernel MCP'yi VS Code CLI içine yükleyin
$ code --add-mcp '{"name":"evokernel","type":"stdio","command":"npx","args":["-y","evo-kernel"]}'EvoKernel MCP'yi Claude Desktop içine yükleyin
claude_desktop_config.json
{
"mcpServers": {
"evokernel": {
"command": "npx",
"args": [
"-y",
"evo-kernel"
]
}
}
}EvoKernel MCP'yi Codex içine yükleyin
$ codex mcp add evokernel -- npx -y evo-kernelEvoKernel MCP'yi Codex config.toml içine yükleyin
~/.codex/config.toml
[mcp_servers.evokernel] command = "npx" args = ["-y", "evo-kernel"]
EvoKernel MCP'yi Gemini CLI içine yükleyin
$ gemini mcp add -s user evokernel npx -- -y evo-kernelEvoKernel MCP'yi Gemini settings.json içine yükleyin
~/.gemini/settings.json
{
"mcpServers": {
"evokernel": {
"command": "npx",
"args": [
"-y",
"evo-kernel"
]
}
}
}EvoKernel MCP araçları 5
README dosyasından algılandıevo_searchevo_inspectevo_runevo_proposeevo_compact
| evo_search | — | |
| evo_inspect | — | |
| evo_run | — | |
| evo_propose | — | |
| evo_compact | — |
Otomatik kontroller
Çalıştırıldı 14 Kas 2026Tam rapor →Henüz doğrulanmadı. Bir sunucunun 80 puana, ciddi bir bulgu olmamasına ve kontrol edebilmemiz için yeterli veriye ihtiyacı vardır. Kontroller nasıl çalışır · Daha fazla puan için nelerin düzeltileceği
- Kaynak deposu bağlantılı ve erişilebilirdamonless/evokernel is public and reachablegithub.com/damonless/evokernel ↗Geçti
- Paket, bu depoyu kaynağı olarak gösteriyorevo-kernel names damonless/evokernel as sourcenpmjs.com/package/evo-kernel ↗Geçti
- Derleme kökeni (Sigstore onayı)No build attestation published for this releaseKontrol edilmedi
- Açık kaynak lisansı (OSI)MITspdx.org/licenses/MIT.html ↗Geçti
- Son bir yıl içinde commit veya sürüm mevcutLast commit or release 2026-11-11github.com/damonless/evokernel ↗Geçti
- OpenSSF ScorecardKontrol edilmedi
- Paket adı popüler bir pakete yakın değilNo popular package one edit away from evo-kernelGeçti
- Pakette veya bağımlılıklarında kritik uyarı yokKontrol edilmedi
- Modele yönelik gizli talimat yok5 tool descriptions and the README read; no override phrases, credential paths or hidden charactersGeçti
- Yıkıcı araçlar etiketlenmişNo tool named like delete, drop or execGeçti
- Uzak uç nokta MCP el sıkışmasına yanıt veriyorKontrol edilmedi
🧬 EvoKernel (evo-kernel)
Stop Repeating the Same Bug Across Coding Sessions — AST-Verified Cognitive Memory & 6-Stage Deterministic Gatekeeper, with 88.7% Lower Session-Start Token Tax and 0 External Dependencies.
The Deterministic Self-Evolving Meta-Kernel & Cognitive Context OS for AI Coding Agents
Claude Code · Cursor · Codex · Windsurf · Cline · Roo · GitHub Copilot · OpenCode · Gemini · Antigravity
English · 简体中文 · 🌐 Product Site · 🖥️ Interactive Workbench Demo · 📊 Benchmarks
What is EvoKernel? EvoKernel gives your AI coding agent cross-session AST-verified cognitive memory, visible 1-line recall receipts (
🛡️ EvoKernel Recall), and a 6-stage deterministic Gatekeeper so fixed bugs stay fixed across sessions — while folding sprawling MCP tool schemas and monolithic rule files behind 5 fixed meta-primitives (-88.7% session-start token tax:27,150 → 3,066tok/turn, 100% KV cache hit, 0 external dependencies).
[!NOTE] Disambiguation Note: EvoKernel (
evo-kernel) is an agent architecture and context engineering framework for AI coding assistants (Claude Code, Cursor, Windsurf, Codex, Gemini, etc.). It is not affiliated with academic ICML papers/benchmarks of similar naming or Linux kernel projects.
⚡ 30-Second Quick Start
Get started in 3 commands — zero installation required:
# 1. Instant Zero-Write X-Ray (<25ms) — scan host rules, git hotspots & memory coverage
npx -y evo-kernel score
# 2. One-Click Safe Wiring & Doctor Check — wire 10 IDEs safely with stealth mode
npx -y evo-kernel init --stealth && npx -y evo-kernel doctor
# (Preview MCP virtualization token savings safely with: npx -y evo-kernel virtualize --dry-run)
# 3. Launch EvoKernel Workbench to inspect capabilities, AST memories & 7-day recall
npx -y evo-kernel ui
💡 Node.js 18 / 20 Instant 1-Liner (No Global Node Upgrade Needed):
npx -y -p node@22 evo-kernel score
(Note:npx -p node@22is recommended for one-off CLI diagnostics. For a persistent background MCP service, upgrade system Node to>= 22.5.0vianvm install 22 && nvm use 22orfnm use 22, and install globally vianpm install -g evo-kernel.)
Why Node.js >= 22.5.0? EvoKernel runs purely on nativenode:sqlite,node:module, andnode:test— providing 0 external npm dependencies and 0 supply-chain vulnerability risk.
# Clone and build from source (takes <50ms, zero npm install required)
git clone https://github.com/damonless/EvoKernel.git
cd EvoKernel
node ./scripts/build.mjs
# Wire L0 Meta-Rule Seed + Single Meta-MCP into your active coding agents
node ./dist/cli/index.js init --targets auto --stealth
# Cold-start mine your repository structure, project stacks & Git fix history
node ./dist/cli/index.js bootstrap --max-commits=50
# Run offline worktree optimization cycle
node ./dist/cli/index.js optimize --dim both -k 3
# CI / Deliverable canonical inspection (.xlsx, .docx, .pptx, .csv, .json, .md)
npx -y evo-kernel check ./README.md
# Inspect capability tree, multi-branch AST memory freshness & live MCP handshake
node ./dist/cli/index.js tree
node ./dist/cli/index.js memory verify
node ./dist/cli/index.js doctor --roi
node ./dist/cli/index.js audit --global
🔒 Reversibility, Team Sharing & Privacy
EvoKernel is designed from the ground up to be safe to trial, transparent to inspect, and completely reversible at any moment:
1. What evo init Touches & 1-Command Lossless Uninstall
When you run npx evo-kernel init, it touches only three isolated surfaces:
- Host Agent Rule Files: Inserts a compact (<1,100 tok), bounded English managed block between
<!-- EVO:START -->and<!-- EVO:END -->markers in detected configuration files (CLAUDE.md,AGENTS.md,.cursor/rules/evo-kernel.mdc, orGEMINI.mdwhen.gemini/is present — avoiding duplicate root Markdown injection). Existing user rules outside these markers are untouched. - Host MCP Configs: Registers a single stdio gateway entry for
evo-kernel(leaving third-party servers untouched unless virtualized). - Workspace
.evo/Tree: Generates local capability and episodic memory directories (.evo/rules/,.evo/skills/,.evo/memories/,.evo/tools/,.evo/.cache/).
To cleanly and completely revert your repository and agent configurations back to baseline, run:
npx -y evo-kernel virtualize --restore && npx -y evo-kernel uninstall
This restores any virtualized MCP servers to host configuration files, strips all <!-- EVO:START --> blocks cleanly, unwires registered lifecycle hooks, and removes .evo/ with zero left-behind configuration artifacts.
2. Multi-Person Team Sharing vs. --stealth Mode
- Multi-Person Team Sharing (Default
evo init): Commit.evo/rules/,.evo/memories/, and.evo/tools/to your Git repository. Every team member and coding agent immediately benefits from shared root-cause bug fixes and verified sandboxed micro-tools, while internal cache files (.evo/.cache/) are automatically gitignored. - Personal Standalone Trial (
evo init --stealth): Appends.evo/and modified host rule files to.git/info/exclude. Git completely ignores EvoKernel files locally without touching.gitignoreor creating uncommitted working tree diffs in shared repositories. Zero git pollution.
3. 100% Local-First & Zero Outbound Telemetry
EvoKernel performs 0 outbound network requests, transmits 0 analytics or telemetry, and requires 0 external cloud APIs. All SQLite FTS5 indexes and observable recall ledgers (.evo/.cache/telemetry.db) are stored 100% locally on your machine.
📈 50-Turn Context-Tax Analytical Model & Live Engine Micro-Benchmark (npm run benchmark)
Analytical cost/cache model across 8 standard MCP servers (github, playwright, kubernetes, docker, linear, postgres, sentry, context7 — 77 tools total) + a mature repo knowledge base (10 rules, 4 skills, 5 micro-tools, 15 debugging memories) over a 50-turn coding session with 3 mid-session capability evolutions, paired with live local engine micro-benchmarks (reproduce locally via npm run benchmark).
Note on zero-prefix-invalidation condition: The 0 mid-session cache invalidation guarantee holds when new capabilities are crystallized as core: false scoped rules, skills, micro-tools, or memory entries (the default in EvoKernel), which reside in .evo/ without mutating the top-level tools/list schema or host CLAUDE.md L0 prefix.
| Metric | Raw Multi-MCP + Monolithic CLAUDE.md |
🧬 EvoKernel 5-Tool Meta-Gateway | Model / Live Result |
|---|---|---|---|
| Exposed Tool Schemas | 77 tools (14,700 tok) |
5 fixed meta-tools (1,916 tok) |
-93.5% schema count (-87.0% schema tok) |
| Session-Start Static Prefix / Turn | 27,150 tokens | 3,066 tokens | -88.7% session-start token tax |
| Mid-Session Cache Invalidations | 3 full prefix busts | 0 (100% cache hit) | 100% KV Cache Shield |
| 50-Turn Cumulative Prompt Tokens | 1,931,250 tokens | 738,570 tokens | -61.8% total token load |
| 50-Turn Cost (Claude Sonnet 4.5) | $1.15 | $0.34 | -70.4% API cost |
| 50-Turn Cost (Claude Opus 4.5) | $5.76 | $1.70 | -70.4% API cost |
| Live Engine AST Verification Speed | Unverified text (drifts silently) | ~0.32 ms / memory | <12ms batch across 36 memories¹ |
¹ Terminology Note: AST Anti-Drift / AST Fingerprinting utilizes Zero-Dep Lexical-Structural Skeleton Fingerprinting, which is immune to comments, code reformatting, and line-number drift without requiring external compiler dependencies.
⚡ Why Most "Self-Improving Agent" Setups Fail After 30 Sessions
Every developer using Claude Code, Cursor, Windsurf, Cline, Roo, Copilot, Codex, OpenCode, Gemini, or Antigravity hits five engineering walls:
- The Slop-Pile Rule Rot (
CLAUDE.mdBloat): Appending"Never do X"every time an agent makes a mistake turns your rules file into a 10,000-token contradictory junk drawer. Past ~1,500 tokens, LLM instruction-following degrades sharply (Lost-in-the-Middle). - Worker Grading Its Own Homework: Letting an LLM directly overwrite global skills or scripts without deterministic verification leads to broken, path-hardcoded scripts being crystallized as "permanent tools."
- The Dynamic MCP Prompt-Cache Collapse: If "evolving MCP tools" means spawning new MCP servers or mutating the top-level
tools/listschema mid-session, you invalidate the LLM's KV Prompt Cache prefix on every mutation—increasing token costs by 5–10x and requiring constant IDE restarts. - Third-Party MCP Sprawl: Adding 10 downstream MCP servers directly to your agent configuration dumps 50–100 tool definitions into every prompt header, diluting tool-calling accuracy and inflating baseline context costs.
- Confounded Causation & Hallucinatory Evolution: Agents mutate rules based on spurious correlation during complex multi-step sessions without isolating whether a rule actually helped, hurt, or was contested by confounding variables.
EvoKernel solves all five with a deterministic local compiler, worktree evolution engine & routing kernel:
📊 Comprehensive Competitive Benchmark Matrix
| Dimension | MemGPT / Letta |
Aider |
Direct MCP Proxies | affaan-m/ECC |
AMAP-ML/SkillClaw |
🧬 EvoKernel v0.3.0 (Ours) |
|---|---|---|---|---|---|---|
| Primary Focus | Stateful conversational agent DB | Git-centric terminal pair programmer | Pass-through MCP aggregation | Static engineering prompt library | Background LLM evolutionary agent | Deterministic self-evolving meta-kernel for coding agents |
| Integration Architecture | Heavy external service / Postgres / Python daemon | Standalone Python CLI replacing developer IDE | Raw JSON-RPC bridge passing all child tools | Preloaded Markdown templates | Hijacks /v1/chat reverse proxy |
Parasitic Meta-MCP + <80-line Seed injected into existing IDEs |
| Runtime Dependencies | Heavy (Postgres, Python, vector DBs) | Python pip packages | Node / Python packages | Zero (plain markdown) | Python FastAPI daemon | 0 Dependencies (Pure Node.js >= 22.5 built-ins: node:sqlite, node:module, node:test) |
| Prompt Cache Stability | Cache-unfriendly (frequent context shifts) | Varies per edit | Destructive (exposing all child tools busts KV prefix on every change) | High context footprint | Neutral | 100% Byte-Stable: Exactly 5 immutable meta-tools exposed to host |
| Downstream MCP Virtualization | None | None | Dumb pass-through (50+ tools in prompt) | None | None | Zero-cache-invalidation FTS5 index + on-demand stdio JSON-RPC proxy |
| Verification & Gatekeeper | Model self-reflection | Git commit diffs & tests | None | Manual /learn-eval |
Async LLM reviewer | 6-Stage Deterministic Gatekeeper (Static Security, Lexical De-Symbol, Sandbox Exit 0, BM25, 1500-tok Cap, Anti-Confounding) |
| Offline Worktree Optimization | None | None | None | None | Cloud LLM evaluations | evo optimize: Isolated Git worktrees, dual inv/dom cycles, automated probe evaluation & regression rollbacks |
| Deliverable Inspection | None | None | None | None | None | Zero-dependency canonical parser for .xlsx, .docx, .pptx, CSV, JSON/JSONL, and Markdown |
| Episodic Memory & Anti-Drift | Semantic vector embeddings (hallucination prone) | Repo map only | None | None (static docs) | No AST verification | Zero-Dep Lexical-Structural Symbol Fingerprinting (Fast regex/lexical AST hash, [STALE] demotion, Topology Penetration Anchors) |
| Workbench & Diagnostic Scoring | Web UI with Postgres | None | None | None | Web UI | evo score (<25ms zero-write scan) & evo ui (0-dep EvoKernel Workbench, dual-mode native client, SSE live-reload, strict CSP, exportable single-file HTML) |
| Causal Telemetry | None | Git diff size | None | None | Win/loss counter | Causal outcomes (helped, hurt, contested) with ERR_CONFOUNDED_CAUSATION protection |
| Multi-Agent Harness Support | Standalone only | Standalone only | Generic MCP clients | Claude Code / Cursor only | Generic proxy | 10 Native Harnesses (Claude, Cursor, Windsurf, Cline, Roo, Copilot, Codex, OpenCode, Gemini, Antigravity) |
| Cold-Start Gene Extraction | Empty until chat sessions accumulate | Git repo scan | Empty | Static catalog | Empty until chat history grows | evo bootstrap mines project stacks + git fixes in <10s |
🧠 Core Architecture & Deep Technical Reference
EvoKernel exposes 5 immutable meta-tools (evo_search, evo_inspect, evo_run, evo_propose, evo_compact) over stdio for 100% KV prompt-cache retention, backed by offline Git worktree optimization, zero-dependency deliverable inspection, causal outcome attribution, and 10-host configuration adapters.
5 Immutable Meta-Tools (stdio JSON-RPC 2.0)
| Meta-Tool | Tier | Purpose |
|---|---|---|
evo_search |
L0 | FTS5 BM25 search across Rules, Skills, Micro-Tools, Virtualized External Tools, and Memories. Performs live Stage-2 AST fingerprint verification and demotes [STALE] memories automatically. |
evo_inspect |
L1 / L2 | Progressive disclosure loader. Delivers Symptom/Root-Cause/Solution triads, JSON Schemas for virtualized external tools, and Topology Penetration Anchors (live line spans, callers, and negative dead-ends). |
evo_run |
Execution | Executes local sandboxed Micro-Tools (.mjs, .py, .ps1, .sh) or proxies calls to downstream MCP servers via McpProxyManager. |
evo_propose |
Evolution | Submits a candidate Rule, Skill, Micro-Tool, or Memory through the 6-Stage Deterministic Gatekeeper (Static Security, Lexical De-Symbol, Sandbox Dry-Run, BM25 Deduplication, Token Budget Cap, Anti-Confounding). |
evo_compact |
GC | Atomically merges fragmented rules or archives [STALE] memories into .evo/archive/ to keep core token consumption under the 1,500-token limit. |
Downstream MCP Proxy Virtualization (evo virtualize)
Host Coding Agent (Claude / Cursor / Copilot / etc.)
│
▼ Fixed 5-Tool stdio Interface (100% Byte-Stable KV Cache)
╔════════════════════════════════════════════════════╗
║ EvoKernel Meta-MCP ║
║ evo_search · evo_inspect · evo_run · propose · compact
╚════════════════════════════════════════════════════╝
│ │
FTS5 BM25 Search Proxy Execution (`evo_run`)
▼ ▼
┌────────────────────┐ ┌─────────────────────────────┐
│ capability_fts │ │ McpProxyManager (Pool) │
│ ext__postgres__... │ └──────────────┬──────────────┘
│ ext__github__... │ │ stdio JSON-RPC
└────────────────────┘ ▼
┌─────────────────────────────┐
│ Downstream MCP Servers │
│ postgres · github · docker │
└─────────────────────────────┘
evo virtualize --dry-run # Preview token savings without modifying files
evo virtualize # Fold third-party stdio MCPs into EvoKernel's dynamic proxy
evo virtualize --restore # Losslessly restore virtualized MCP servers back to host configs
Universal Hook Router (evo hook <event>)
evo hook post-tool --tool Edit --file src/core/storage.ts # Track mutations, >=10 diagnostic reads & scoped rules
evo hook stop # Emit crystallization & anti-poisoning dirty alerts
evo hook pre-commit # Block leaked caches or >1,500-token core budget
evo hook mark-recovery # Record recovery telemetry after command failures
# Run offline optimization across both Invariant and Domain dimensions
evo optimize --dim both -k 3
EvoKernel MCP soruları
EvoKernel MCP'yi Claude Code'a nasıl eklerim?
Terminalinizde claude mcp add evokernel -- npx -y evo-kernel komutunu çalıştırın. Her projede kullanılabilir olması için --scope user ekleyin.
EvoKernel MCP'yi Cursor'a nasıl eklerim?
~/.cursor/mcp.json dosyasını açın ve yukarıdaki yükleme bölümünde gösterilen Cursor yapılandırmasını kullanarak sunucuyu mcpServers altına ekleyin.
EvoKernel MCP hangi araçları sunar?
5 araç sunar; bunlar arasında evo_search, evo_inspect, evo_run, evo_propose, evo_compact yer alır.
EvoKernel nedir?
EvoKernel; Claude Code, Cursor ve Windsurf gibi yapay zeka kodlama asistanları için geliştirilmiş bir ajan mimarisi ve bağlam mühendisliği (context engineering) çerçevesidir.
EvoKernel'i nasıl kaldırabilir ve yapılandırmalarımı geri alabilirim?
virtualize --restore ve uninstall komutlarını çalıştırarak deponuzu (repository) ve ajan yapılandırmalarınızı tamamen eski haline getirebilirsiniz.
EvoKernel gizlilik ve verileri nasıl yönetir?
Dışarıya veri gönderimi (outbound telemetry) yapmayan, tüm indeksleri ve geri çağırma defterlerini (recall ledgers) yerel makinenizde saklayan, öncelikli olarak yerel çalışan (local-first) bir sistemdir.