P
p-funk/fegis
Define tools in YAML and store each call in Qdrant
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
我们没有从该仓库取到可核对的安装命令,也没有公开的远端端点。这两样都没有时,我们不出配置——编一条出来比不给更糟。 各客户端的接法 →
- 来源明细
- 收录自 abordage/awesome-mcp 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
- 收录与活跃
- 收录于 2026-11-05 · 最近见到 2026-11-14 · 共见到 10 次 · 被 10 个来源列出
- 评分构成
- 综合分 1,003 · 10 个来源 · mcp
常见问题(答案都来自我们的记录)
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
我们收录于 2026-11-05;最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
# Fegis
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
Fegis does 3 things:
1. Easy to write tools - Write prompts in YAML format. Tool schemas use flexible natural language instructions.
2. Structured data from tool calls saved in a vector database - Every tool use is automatically stored in Qdrant with full context.
3. Search - AI can search through all previous tool usage using semantic similarity, filters, or direct lookup.
## Quick Start
bash
# Install uv
# Windows
winget install --id=astral-sh.uv -e
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Clone
git clone https://github.com/p-funk/fegis.git
# Start Qdrant
docker run -d --name qdrant -p 6333:6333 -p 6334:6334 qdrant/qdrant:latest
## Configure Claude Desktop
Update claudedesktopconfig.json:
json
"mcpServers": {
"fegis": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/fegis",
"run",
"fegis"
],
"env": {
"QDRANTURL": "http://localhost:6333",
"QDRANTAPIKEY": "",
"COLLECTIONNAME": "fegismemory",
"EMBEDDINGMODEL": "BAAI/bge-small-en",
"ARCHETYPEPATH": "/absolute/path/to/fegis-wip/archetypes/default.yaml",
"AGENTID": "claudedesktop"
Restart Claude Desktop. You'll have 7 new tools available including SearchMemory.
## How It Works
### 1. Tools from YAML
yaml
parameters:
BiasScope:
description: "Range of bias detection to apply"
examples: [confirmation, availability, anchoring, systematic, comprehensive]
IntrospectionDepth:
description: "How deeply to examine internal reasoning processes"
examples: [surface, moderate, deep, exhaustive, metarecursive]
tools:
BiasDetector:
description: "Identify reasoning blind spots, cognitive biases, and systematic errors in AI thinking patterns through structured self-examination"
parameters:
BiasScope:
IntrospectionDepth:
frames:
identifiedbiases:
type: List
required: true
reasoningpatterns:
type: List
required: true
alternativeperspectives:
type: List
required: true
### 2. Automatic Memory Storage
Every tool invocation gets stored with:
Tool name and parameters used
Complete input and output
Timestamp and session context
Vector embeddings for semantic search
### 3. SearchMemory Tool
"Use SearchMemory and find my analysis of privacy concerns"
"Use SearchMemory and what creative ideas did I generate last week?"
"Use SearchMemory and show me all UncertaintyNavigator results"
"Use SearchMemory and search for memories about decision-making"
## Available Archetypes
archetypes/default.yaml - Cognitive analysis tools (UncertaintyNavigator, BiasDetector, etc.)
archetypes/simpleexample.yaml - Basic example tools
archetypes/emojimind.yaml - Symbolic reasoning with emojis
1. Easy to write tools - Write prompts in YAML format. Tool schemas use flexible natural language instructions.
2. Structured data from tool calls saved in a vector database - Every tool use is automatically stored in Qdrant with full context.
3. Search - AI can search through all previous tool usage using semantic similarity, filters, or direct lookup.
## Quick Start
bash
# Install uv
# Windows
winget install --id=astral-sh.uv -e
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Clone
git clone https://github.com/p-funk/fegis.git
# Start Qdrant
docker run -d --name qdrant -p 6333:6333 -p 6334:6334 qdrant/qdrant:latest
## Configure Claude Desktop
Update claudedesktopconfig.json:
json
"mcpServers": {
"fegis": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/fegis",
"run",
"fegis"
],
"env": {
"QDRANTURL": "http://localhost:6333",
"QDRANTAPIKEY": "",
"COLLECTIONNAME": "fegismemory",
"EMBEDDINGMODEL": "BAAI/bge-small-en",
"ARCHETYPEPATH": "/absolute/path/to/fegis-wip/archetypes/default.yaml",
"AGENTID": "claudedesktop"
Restart Claude Desktop. You'll have 7 new tools available including SearchMemory.
## How It Works
### 1. Tools from YAML
yaml
parameters:
BiasScope:
description: "Range of bias detection to apply"
examples: [confirmation, availability, anchoring, systematic, comprehensive]
IntrospectionDepth:
description: "How deeply to examine internal reasoning processes"
examples: [surface, moderate, deep, exhaustive, metarecursive]
tools:
BiasDetector:
description: "Identify reasoning blind spots, cognitive biases, and systematic errors in AI thinking patterns through structured self-examination"
parameters:
BiasScope:
IntrospectionDepth:
frames:
identifiedbiases:
type: List
required: true
reasoningpatterns:
type: List
required: true
alternativeperspectives:
type: List
required: true
### 2. Automatic Memory Storage
Every tool invocation gets stored with:
Tool name and parameters used
Complete input and output
Timestamp and session context
Vector embeddings for semantic search
### 3. SearchMemory Tool
"Use SearchMemory and find my analysis of privacy concerns"
"Use SearchMemory and what creative ideas did I generate last week?"
"Use SearchMemory and show me all UncertaintyNavigator results"
"Use SearchMemory and search for memories about decision-making"
## Available Archetypes
archetypes/default.yaml - Cognitive analysis tools (UncertaintyNavigator, BiasDetector, etc.)
archetypes/simpleexample.yaml - Basic example tools
archetypes/emojimind.yaml - Symbolic reasoning with emojis
收录徽章(可选)
想把收录标记放进 README 就复制这行,可选,不影响收录。
[](https://anclum.com/zh/s/p-funk-fegis/)
- 来源
- awesome · https://github.com/p-funk/fegis
- 按领域浏览
- MCP 服务
- 收录来源
- 10 个独立来源
- 收录于
- 今天
同类推荐
所属领域与标签
每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。