About MetaGO Algorithms
MetaGO Algorithms is an MCP server that makes 927 algorithms available through 57 tools across 14 trigger categories. It supports algorithm execution and discovery alongside analyses such as coupling, value, distance, correlation, dimensionality reduction, and security.
Key features
- 01Execute algorithms by name and parameters
- 02Search and inspect algorithm metadata
- 03Coupling and multidimensional value analysis
- 04Distance metrics and correlation analysis
- 05Dimensionality reduction and security audits
Use cases
- 01Finding an algorithm for a task
- 02Comparing vector similarity or distance
- 03Assessing coupling and multidimensional value
- 04Running correlation or security analysis
MCP support
Exposes 57 tools backed by 927 algorithms to MCP-compatible agents. The tools cover algorithm execution, discovery, statistics, and specialized analysis.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
57Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| input | object | Yes | Algorithm input parameters |
| operation | string | No | Operation type (algorithm-name keyword), e.g. cosine/euclidean/pearson |
Details
From the project README@metago-ai/algorithms — 927 算法 MCP 服务器
MetaGO Intelligent Lifeform 的算法核心 — 57 工具 / 927 算法 / 14 触发大类 / 4 层架构,Engine V2.1.0 硬驱动。
What it is
@metago-ai/algorithms is the algorithmic backbone of the MetaGO Intelligent Lifeform. It exposes 57 MCP tools backed by 927 algorithms across 14 trigger categories, organized in a 4-layer architecture. Every tool is hard-driven by @metago-ai/[email protected] (KMWI memory + evolution engine + skill generator).
This is not a library of math functions. It is a Model Context Protocol (MCP) server that gives any MCP-compatible AI agent (Trae, Claude Code, Codex, Cursor, etc.) real-time access to coupling calculation, value assessment, distance metrics, correlation analysis, dimensionality reduction, security audit, frequency processing, and 7 more trigger categories.
Architecture — 4 layers / 14 trigger categories
| Layer | Name | Tools | Algorithms | Trigger Categories |
|---|---|---|---|---|
| L1 | 通用入口层 (General Entry) | 3 | 9 | 3 |
| L2 | 检索发现层 (Retrieval & Discovery) | 4 | 18 | 4 |
| L3 | 高频专用层 (High-Frequency Specialized) | 30 | 540 | 4 |
| L4 | 族级工具层 (Family Tools) | 20 | 360 | 3 |
| Total | — | 57 | 927 | 14 |
The 14 trigger categories
| # | Category | Layer | Trigger condition |
|---|---|---|---|
| 1 | Algorithm execution | L1 | Agent needs to execute an algorithm |
| 2 | Algorithm retrieval | L1 | Agent needs to find an algorithm by name/family/capability |
| 3 | Statistics | L1 | Agent needs server statistics |
| 4 | Family listing | L2 | Agent needs to list algorithm families |
| 5 | Algorithm search | L2 | Agent needs semantic search over algorithms |
| 6 | Info lookup | L2 | Agent needs detailed info on a specific algorithm |
| 7 | Proactive suggestion | L2 | Agent needs algorithm recommendations for a task |
| 8 | Coupling calculation | L3 | Task involves relationship strength / coupling degree |
| 9 | Value assessment | L3 | Task involves multi-dimensional value scoring |
| 10 | Distance metrics | L3 | Task involves similarity / distance between vectors |
| 11 | Correlation analysis | L3 | Task involves statistical correlation |
| 12 | Dimensionality reduction | L3 | Task involves PCA / SVD / feature reduction |
| 13 | Security audit | L3 | Task involves vulnerability / security assessment |
| 14 | Frequency processing | L3 | Task involves frequency-domain analysis |
Install
npm install @metago-ai/algorithms
Use as MCP server
Trae / Claude Code / Cursor / any MCP client
Add to your MCP client config:
{
"mcpServers": {
"metago-algorithms": {
"command": "node",
"args": ["node_modules/@metago-ai/algorithms/index.js"]
}
}
}
Standalone
npx @metago-ai/algorithms
# or
node node_modules/@metago-ai/algorithms/index.js
Tool list (57 tools)
L1 — General Entry (3 tools)
execute— Execute any algorithm by name with parametersexecute_sync— Synchronous algorithm executionget_statistics— Server statistics (tool count, algorithm count, layer distribution)
L2 — Retrieval & Discovery (4 tools)
list_algorithms— List all 927 algorithms with metadatalist_families— List 14 algorithm familiessearch_algorithms— Semantic search over algorithm descriptionsget_algorithm_info— Detailed info on a specific algorithm
L3 — High-Frequency Specialized (30 tools)
Coupling (8 tools)
coupling_calculate·coupling_clustering·coupling_trend·normalize_couplingbuild_coupling_matrix·sort_coupling_scores·is_superconductive·cooccurrence_frequency
Value Assessment (3 tools)
value_assess·build_value_vector·evaluate_bidirectional
Distance Metrics (6 tools)
euclidean_distance·manhattan_distance·chebyshev_distancecosine_similarity·dice_coefficient·jaccard_coefficient
Correlation (4 tools)
pearson_correlation·spearman_correlation·kendall_tau·covariance
Dimensionality Reduction (3 tools)
extract_pca·simplified_svd·reduce_dimension
Security & Audit (3 tools)
security_assess·audit_check·bias_detect
Frequency & Time (3 tools)
frequency_process·time_analyze·time_decay_cooccurrence
L4 — Family Tools (20 tools)
Fuzzy & Semantic (3 tools)
fuzzy_string_match·semantic_similarity·weighted_cosine
Reasoning (3 tools)
reasoning_chain·logic_reason·conflict_resolve
Asymmetry & Symmetry (3 tools)
detect_asymmetry·record_symmetric·identify_strong_pairs·identify_weak_pairs
Negentropy (1 tool)
negentropy_measure
Intuition (1 tool)
intuition_gauge
Lifeform Operations (8 tools)
memory_operate·learning_learn·creation_create·evolution_evolvedecision_decide·dialog_manage·idea_generate·proactive_suggest
Engine dependency
This package is hard-driven by @metago-ai/[email protected]:
- KMWI Memory — 4-layer memory (Knowledge → Memory → Wisdom → Intuition) backs algorithm state
- EvolutionEngine — 5-stage meta-evolution can generate new algorithms on demand
- DecisionLock — 4-gate verification before every algorithm output
- SkillGenerator — generates new algorithm SKILL.md files from internal patterns
License
MIT © 2026 易霄 / 元构光年(成都)人工智能科技有限公司
Links
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.