claude-101
27 AI tools as MCP server + CLI + Skill. Just talk to Claude — it handles the rest.
What is this?
Install once, get 24 superpowers. Claude 101 is an MCP server that gives Claude real computation abilities — statistics, code analysis, SQL parsing, financial math, and more — things LLMs cannot do reliably on their own.
How it works:
You: "Compare React, Vue, and Svelte for our project"
↓
Skill tells Claude to call build_comparison_matrix
↓
MCP tool computes: Vue 8.1 > React 7.9 > Svelte 7.5 (weighted scoring)
↓
Claude writes: "Vue leads by 0.2 points. The result is sensitive to
the DX weight — if you value Ecosystem more, React wins."
Without claude-101: Claude guesses at numbers and rankings. With claude-101: Claude uses precise computation, then reasons about the results.
Setup (2 minutes)
Step 1: Add MCP Server
Add to your .mcp.json (project root or ~/.claude/.mcp.json):
{
"mcpServers": {
"claude-101": {
"command": "uvx",
"args": ["--from", "claude-101[mcp]", "claude-101-server"]
}
}
}
Step 2: Install Skill
The Skill teaches Claude when to call each tool and how to use every field in the result:
mkdir -p ~/.claude/skills/claude-101-mastery/references
cd ~/.claude/skills/claude-101-mastery
BASE=https://raw.githubusercontent.com/claude-world/claude-101/main/skills/claude-101-mastery
curl -sLO $BASE/SKILL.md
curl -sLO $BASE/references/writing-workflows.md --output-dir references
curl -sLO $BASE/references/analysis-workflows.md --output-dir references
curl -sLO $BASE/references/coding-workflows.md --output-dir references
curl -sLO $BASE/references/business-workflows.md --output-dir references
Done. Start a new Claude Code session and just talk naturally.
24 Use Cases
After setup, you can simply ask Claude to do any of these — the Skill handles the rest:
Writing & Communication
| # | You say... | Claude calls | What you get |
|---|---|---|---|
| 1 | "Write a follow-up email to the client" | draft_email |
Email with computed formality score, Flesch readability, tone analysis, pre-send checklist |
| 2 | "Plan a blog post about FastAPI" | draft_blog_post |
Outline with word targets per section, SEO fields, keyword analysis, heading validation |
| 3 | "Organize these meeting notes" | parse_meeting_notes |
Extracted attendees, action items with owners + deadlines, decisions, topics |
| 4 | "Create a Threads post for this launch" | format_social_content |
Platform-formatted text, character count check, hashtags, engagement signals |
| 5 | "Write a README for this project" | scaffold_tech_doc |
Template + code structure analysis, completeness scoring, effort estimate |
| 6 | "Help me structure this novel" | structure_story |
Story beats with word targets, tension curve, pacing/dialogue/transition analysis |
Analysis & Research
| # | You say... | Claude calls | What you get |
|---|---|---|---|
| 7 | "Analyze this CSV data" | analyze_data |
Per-column statistics, Pearson correlations, IQR outlier detection |
| 8 | "Summarize this 10-page report" | summarize_document |
Key sentences (algorithmically scored), Flesch readability, keyword frequency |
| 9 | "Compare these 3 frameworks" | build_comparison_matrix |
Weighted ranking with scores, winner + margin, sensitivity analysis |
| 10 | "Analyze our survey results" | analyze_survey |
Per-question stats, NPS score (promoter/passive/detractor), satisfaction % |
| 11 | "Review this quarter's financials" | analyze_financials |
Gross/operating/net margins, growth rates, burn rate, cash runway |
| 12 | "Check this contract for issues" | review_legal_document |
18+ clause detection, missing clause alerts, complexity score, risk levels |
Coding & Technical
| # | You say... | Claude calls | What you get |
|---|---|---|---|
| 13 | "Scaffold a UserService class" | scaffold_code |
Description-aware code (CRUD/API/auth patterns), 6 languages x 8 patterns |
| 14 | "Review this code for issues" | analyze_code |
Cyclomatic complexity, nesting depth, magic numbers, quality grade A-F |
| 15 | "Explain and optimize this SQL" | process_sql |
Formatted query, execution plan, performance hints (SELECT *, index usage) |
| 16 | "Generate API docs for these endpoints" | scaffold_api_doc |
OpenAPI YAML/Markdown, consistency check, auth detection from code |
| 17 | "Write tests for this function" | generate_test_cases |
Signature parsing, happy/edge/boundary cases, coverage analysis |
| 18 | "Should we use Kafka or SQS?" | create_adr |
ADR with tech knowledge base (28 technologies), differentiated trade-offs |
Business & Productivity
| # | You say... | Claude calls | What you get |
|---|---|---|---|
| 19 | "Plan this 8-week project" | plan_project |
WBS with hours, milestones, critical path, risks, resource allocation |
| 20 | "Prepare me for this interview" | prepare_interview |
Role-specific questions, STAR validation, JD skill extraction, time allocation |
| 21 | "Write a business proposal" | scaffold_proposal |
AIDA framework, ROI/NPV calculation, argument strength analysis |
| 22 | "Handle this angry customer" | build_support_response |
Issue classification, escalation risk 0-100, resolution estimate, quality scoring |
| 23 | "Create a PRD for this feature" | scaffold_prd |
User stories, MoSCoW prioritization, completeness scoring, dependency detection |
| 24 | "Help me decide between these options" | evaluate_decision |
Weighted scoring matrix, rankings, sensitivity analysis |
CLI Usage
Also works as a standalone command-line tool:
# Install
pip install "claude-101[mcp]"
# List all tools
claude-101 list
claude-101 list --category analysis
# Run any tool directly
claude-101 draft-email "meeting follow-up" --tone assertive
claude-101 --pretty analyze-data "name,score\nAlice,95\nBob,87"
claude-101 scaffold-proposal business "Cloud Migration" --investment 100000 --annual-return 50000
# Pipe from stdin
echo "SELECT * FROM users" | claude-101 process-sql -
cat mycode.py | claude-101 analyze-code -
# Tool help
claude-101 draft-email --help
Python Library
from claude_101.analysis.data import analyze_data
from claude_101.business.decision import evaluate_decision
result = analyze_data("name,score\nAlice,95\nBob,87", output_format="csv", operations="all")
result["correlations"] # [{"column_a": "score", "column_b": "hours", "pearson_r": 0.94}]
result = evaluate_decision("A,B", "Speed,Cost", "0.6,0.4", "A:Speed=9,Cost=5;B:Speed=6,Cost=9")
result["winner"] # {"option": "A", "score": 7.4, "margin": 0.2}
Architecture
claude-101/
src/claude_101/
server.py # MCP server (27 tools via FastMCP)
cli.py # CLI (auto-generated from function signatures)
_utils.py # 14 shared computation functions
_guides.py # 24 embedded use-case guides
writing/ # 6 tools: email, blog, meeting, social, techdoc, story
analysis/ # 6 tools: data, summary, comparison, survey, financial, legal
coding/ # 6 tools: codegen, review, sql, apidoc, testgen, adr
business/ # 6 tools: planning, interview, proposal, support, prd, decision
skills/
claude-101-mastery.md # Skill file (teaches Claude how to use all 24 tools)
tests/ # 157 tests across 6 files
Dependencies: Only sqlparse (everything else is stdlib). MCP is optional.
Contributing
See CONTRIBUTING.md for guidelines. See CHANGELOG.md for release history.
License
MIT — see LICENSE.
Metadata
Release files for claude-101 0.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| claude_101-0.2.2.tar.gz | 166.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| claude_101-0.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 319.7 kB
Release files / claude_101-0.2.2.tar.gz
| Download URL | claude_101-0.2.2.tar.gz |
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| Size | 166.4 kB |
| Tags | Source |
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| Uploaded via |
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