EvoKernel MCP server
Commit 14. Nov. 2026Bietet KI-Coding-Agents AST-verifizierten kognitiven Speicher und ein deterministisches Meta-Gateway, um Token-Kosten zu senken und wiederkehrende Bugs zu verhindern.
Auch bekannt als damonless/EvoKernel, evo-kernel
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- Neueste Version
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- Letzter Commit
- 14. Nov. 2026
- Lizenz
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Was ist EvoKernel MCP?
EvoKernel ist ein MCP server. Bietet KI-Coding-Agents AST-verifizierten kognitiven Speicher und ein deterministisches Meta-Gateway, um Token-Kosten zu senken und wiederkehrende Bugs zu verhindern. Er stellt 5 Tools bereit, etwa evo_search, evo_inspect, evo_run.
Zusammenfassung generiert aus dem README des Projekts
Über EvoKernel MCP server
EvoKernel bietet KI-Coding-Agents AST-verifizierten kognitiven Speicher und ein deterministisches Meta-Gateway, um wiederkehrende Bugs zu verhindern und Token-Kosten zu senken. Es wurde für Entwickler konzipiert, die Tools wie Claude Code, Cursor, Windsurf, Cline und GitHub Copilot nutzen. Durch das Zusammenfassen von weitläufigen MCP-Tool-Schemas und monolithischen Rule-Files in fünf feste Meta-Primitives wird die Token-Last beim Session-Start erheblich gesenkt und eine KV-Cache-Hitrate von 100% aufrechterhalten.
Das System arbeitet lokal ohne externe Abhängigkeiten oder ausgehende Netzwerk-Requests, was Privatsphäre und null Supply-Chain-Risiko garantiert. Nutzer können die Umgebung über npx-Befehle initialisieren, um Host-Rules zu scannen, IDEs im Stealth-Modus zu verbinden oder den EvoKernel Workbench zu starten, um AST-Memories und die Recall-Historie zu inspizieren. Es verwaltet den Context über ein lokales .evo-Verzeichnis, das Rules, Skills und Memories enthält, sodass Teams Bugfixes via Git teilen können, während Cache-Dateien privat bleiben.
Was du damit machen kannst
- 1Verhindern von wiederkehrenden Coding-FehlernEin KI-Agent kann AST-verifizierten Speicher nutzen, um sicherzustellen, dass ein Bug, sobald er behoben wurde, über verschiedene Coding-Sessions hinweg behoben bleibt.
- 2Senkung der LLM API-AusgabenEntwickler können ihre gesamte Token-Last und API-Kosten senken, indem sie das Meta-Gateway zur Komprimierung von Tool-Schemas nutzen.
- 3Projekt-Intelligence im Team teilenTeams können verifizierte Memory- und Tool-Verzeichnisse in ein Repository committen, damit jedes Mitglied von gemeinsam genutzten Root-Cause-Fixes profitiert.
- 4Audit von Agenten-Capabilities und MemoryDu kannst den visuellen Workbench nutzen, um die Aktualität von Multi-Branch AST-Memory und Live-MCP-Handshakes zu inspizieren.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
So installierst du EvoKernel MCP
Formate geprüft am 10. Nov. 2026Zu Cursor hinzufügenZu Goose hinzufügenEvoKernel MCP in Claude Code installieren
$ claude mcp add evokernel -- npx -y evo-kernelEvoKernel MCP in Cursor installieren
~/.cursor/mcp.json
{
"mcpServers": {
"evokernel": {
"command": "npx",
"args": [
"-y",
"evo-kernel"
]
}
}
}EvoKernel MCP in VS Code installieren
.vscode/mcp.json
{
"servers": {
"evokernel": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"evo-kernel"
]
}
}
}EvoKernel MCP in VS Code CLI installieren
$ code --add-mcp '{"name":"evokernel","type":"stdio","command":"npx","args":["-y","evo-kernel"]}'EvoKernel MCP in Claude Desktop installieren
claude_desktop_config.json
{
"mcpServers": {
"evokernel": {
"command": "npx",
"args": [
"-y",
"evo-kernel"
]
}
}
}EvoKernel MCP in Codex installieren
$ codex mcp add evokernel -- npx -y evo-kernelEvoKernel MCP in Codex config.toml installieren
~/.codex/config.toml
[mcp_servers.evokernel] command = "npx" args = ["-y", "evo-kernel"]
EvoKernel MCP in Gemini CLI installieren
$ gemini mcp add -s user evokernel npx -- -y evo-kernelEvoKernel MCP in Gemini settings.json installieren
~/.gemini/settings.json
{
"mcpServers": {
"evokernel": {
"command": "npx",
"args": [
"-y",
"evo-kernel"
]
}
}
}EvoKernel MCP tools 5
Erkannt aus dem READMEevo_searchevo_inspectevo_runevo_proposeevo_compact
| evo_search | — | |
| evo_inspect | — | |
| evo_run | — | |
| evo_propose | — | |
| evo_compact | — |
Automatisierte Checks
Geluften am 14. Nov. 2026Vollständiger Bericht →Noch nicht verifiziert. Ein Server benötigt einen Score von 80, keine kritischen Befunde und genug Daten für unsere Prüfung. Wie die Checks funktionieren · Was du für mehr Punkte verbessern kannst
- Source Repository verknüpft und erreichbardamonless/evokernel is public and reachablegithub.com/damonless/evokernel ↗Bestanden
- Paket nennt dieses Repository als Quelleevo-kernel names damonless/evokernel as sourcenpmjs.com/package/evo-kernel ↗Bestanden
- Build-Provenienz (Sigstore-Attestierung)No build attestation published for this releaseNicht geprüft
- Open Source Lizenz (OSI)MITspdx.org/licenses/MIT.html ↗Bestanden
- Commit oder Release im letzten JahrLast commit or release 2026-11-11github.com/damonless/evokernel ↗Bestanden
- OpenSSF ScorecardNicht geprüft
- Package-Name ähnelt keinem populären PackageNo popular package one edit away from evo-kernelBestanden
- Keine kritischen Advisories im Paket oder seinen AbhängigkeitenNicht geprüft
- Keine versteckten Anweisungen an das Modell5 tool descriptions and the README read; no override phrases, credential paths or hidden charactersBestanden
- Destruktive Tools sind markiertNo tool named like delete, drop or execBestanden
- Remote-Endpoint beantwortet den MCP-HandshakeNicht geprüft
README
Auf GitHub ansehen🧬 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 Fragen
Wie füge ich EvoKernel MCP zu Claude Code hinzu?
Führe claude mcp add evokernel -- npx -y evo-kernel in deinem Terminal aus. Füge --scope user hinzu, damit der Server in jedem Projekt verfügbar ist.
Wie füge ich EvoKernel MCP zu Cursor hinzu?
Öffne ~/.cursor/mcp.json und füge den Server unter mcpServers hinzu, mit der Cursor-Config aus dem Installationsabschnitt oben.
Welche Tools bietet EvoKernel MCP?
Er stellt 5 Tools bereit, darunter evo_search, evo_inspect, evo_run, evo_propose, evo_compact.
Was ist EvoKernel?
EvoKernel ist eine Agenten-Architektur und ein Context-Engineering-Framework für KI-Coding-Assistenten wie Claude Code, Cursor und Windsurf.
Wie kann ich EvoKernel deinstallieren und meine Konfigurationen rückgängig machen?
Du kannst dein Repository und deine Agenten-Konfigurationen vollständig rückgängig machen, indem du die Befehle virtualize --restore und uninstall ausführst.
Wie geht EvoKernel mit Datenschutz und Daten um?
Es ist ein Local-first-System ohne ausgehende Telemetrie, das alle Indizes und Recall-Ledger lokal auf deinem Rechner speichert.