Tradingview MCP
atilaahmettaner/tradingview-mcp
AI Trading Intelligence — live prices, 30+ technical indicators, backtesting (6 strategies), walk-forward overfitting detection, trade logs, equity curves, licensed news sentiment (Marketaux), and…
Retrieve market capitalization data for a single company using Octagon MCP.
$ npx skills add OctagonAI/skills --skill company-market-cap -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OctagonAI/skills company-market-cap --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/company-market-cap .claude/skills/company-market-cap && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "company-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/company-market-cap into .claude/skills/company-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-market-cap", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/OctagonAI/skills/tree/main/skills/company-market-capType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add OctagonAI/skills --skill company-market-cap -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OctagonAI/skills company-market-cap --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/company-market-cap .agents/skills/company-market-cap && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "company-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/company-market-cap into .agents/skills/company-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-market-cap", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OctagonAI/skills --skill company-market-cap -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OctagonAI/skills company-market-cap --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/company-market-cap .cursor/skills/company-market-cap && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "company-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/company-market-cap into .cursor/skills/company-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-market-cap", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/OctagonAI/skills.git --path skills/company-market-cap--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add OctagonAI/skills --skill company-market-cap -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OctagonAI/skills company-market-cap --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/company-market-cap .gemini/skills/company-market-cap && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "company-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/company-market-cap into .gemini/skills/company-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-market-cap", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install OctagonAI/skills company-market-capInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add OctagonAI/skills --skill company-market-cap -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/company-market-cap .github/skills/company-market-cap && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "company-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/company-market-cap into .github/skills/company-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-market-cap", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OctagonAI/skills --skill company-market-cap -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install OctagonAI/skills company-market-cap --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/company-market-cap .opencode/skills/company-market-cap && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "company-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/company-market-cap into .opencode/skills/company-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-market-cap", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
company-market-capRetrieve market capitalization data for a single company using Octagon MCP.
Company Market Cap is an agent skill from OctagonAI/skills. Retrieve market capitalization data for a single company using Octagon MCP. Use when you need the current market value, valuation context, or size classification for any publicly traded stock.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `README.md`, `marketplace.json` and `references/interpreting-results.md`).
It sits in Business, Finance & HR, covering MCP servers. It works with Model Context Protocol. The repository describes itself as: A collection of Claude skills for agentic financial research by Octagon. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 51e938c. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are json).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Company Market Cap loads about 1.5k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 53 tokens; SKILL.md has 519 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from OctagonAI/skills at commit 51e938c, republished under its MIT licence (© OctagonAI). 519 words, ~1,543 tokens.
.claude/skills/company-market-cap/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.Retrieve the current market capitalization for a single company using the Octagon MCP server.
Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.
Determine the ticker symbol for the company you want to analyze (e.g., AAPL, MSFT, GOOGL).
Use the octagon-agent tool with a natural language prompt:
Get market capitalization data for the symbol <TICKER>.MCP Call Format:
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Get market capitalization data for the symbol AAPL."
}
}The agent returns precise market cap data:
| Date | Market Capitalization (USD) |
|---|---|
| 2026-02-02 | $3,968,586,877,215.00 |
Additional context provided:
Data Sources: octagon-stock-data-agent
See references/interpreting-results.md for guidance on:
Basic Query:
Get market capitalization data for the symbol AAPL.With Context:
What is the current market cap for Tesla?Historical Reference:
What is Microsoft's market capitalization and how has it changed recently?Valuation Context:
What is NVDA's market cap and how does it compare to other chipmakers?Size Classification:
What size category is AMD based on its market cap?Market Cap = Current Share Price × Shares Outstanding| Aspect | Description |
|---|---|
| Total Value | Market's valuation of all shares |
| Size Indicator | Company scale and influence |
| Index Weight | Determines index composition |
| Acquisition Cost | Theoretical buyout price |
| Misconception | Reality |
|---|---|
| Intrinsic Value | Market perception, not fundamental worth |
| Book Value | Different from accounting value |
| Enterprise Value | Excludes debt and cash |
| Sale Price | Acquisitions often have premiums |
| Category | Range | Characteristics |
|---|---|---|
| Mega-cap | >$200B | Global leaders, household names |
| Large-cap | $10B-$200B | Established, stable companies |
| Mid-cap | $2B-$10B | Growth potential, moderate risk |
| Small-cap | $300M-$2B | Higher growth, higher volatility |
| Micro-cap | $50M-$300M | Speculative, limited coverage |
| Nano-cap | <$50M | Highest risk, low liquidity |
| Threshold | Significance |
|---|---|
| >$1T | Elite status, massive scale |
| >$2T | Global economic influence |
| >$3T | Among world's most valuable |
| Ratio | Formula | Purpose |
|---|---|---|
| P/E | Market Cap / Net Income | Earnings valuation |
| P/S | Market Cap / Revenue | Revenue valuation |
| P/B | Market Cap / Book Value | Asset valuation |
| PEG | P/E / Growth Rate | Growth-adjusted value |
| Metric | Calculation |
|---|---|
| Enterprise Value | Market Cap + Debt - Cash |
| EV/EBITDA | EV / Operating earnings |
| EV/Revenue | EV / Total revenue |
| Question | Purpose |
|---|---|
| Largest in sector? | Market leadership |
| Above/below median? | Relative positioning |
| Gap to leader? | Distance from top |
| Timeframe | Analysis |
|---|---|
| 1 Year | Recent performance |
| 5 Years | Medium-term trend |
| 10 Years | Long-term growth |
| All-time High | Peak valuation |
| Comparison | Purpose |
|---|---|
| vs. Global Leaders | Scale perspective |
| vs. Country GDP | Economic significance |
| vs. Index Total | Market weight |
| Factor | Impact |
|---|---|
| Earnings | Fundamental driver |
| Growth | Future expectations |
| Sentiment | Market psychology |
| Macro | Economic conditions |
| Event | Effect |
|---|---|
| Buybacks | Reduces shares, concentrates value |
| Issuance | Increases shares, dilutes |
| Stock Split | No effect (price adjusts) |
| Spin-offs | Separates value |
What is the market cap for XYZ and how does it compare to peers?What is the market capitalization of my largest holding, AAPL?Apple's market cap after today's earnings announcement?Is TSLA's market cap justified relative to its revenue?Use precise values: Full number for calculations, rounded for communication.
Note the date: Market cap changes constantly with price.
Consider float: Some shares may not be tradeable.
Compare appropriately: Same industry, similar business models.
Understand drivers: Price appreciation vs. share changes.
Enterprise value: Add debt consideration for M&A context.
| Skill | Combined Use |
|---|---|
| stock-quote | Market cap + current price details |
| batch-market-cap | Single company vs. peer group |
| income-statement | Market cap vs. earnings |
| balance-sheet | Market cap vs. book value |
| financial-metrics-analysis | Full valuation analysis |
© OctagonAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 4 other files (references) in skills/company-market-cap of OctagonAI/skills.
Open the folder on GitHubat commit 51e938c
Company Market Cap next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Company Market Cap this skillOctagonAI/skills | 127 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Okx Cex Marketdex-original/okx-agent-trade-kit | 110 | 1 repos | ~2.7k | Automated safety check: Pass | MIT | |
| Polymarket Tennislivetennisapi/livetennisapi-mcp | 152 | — | ~3k | Automated safety check: Pass | MIT | |
| Okx Sentiment Trackerdex-original/okx-agent-trade-kit | 110 | 1 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Odoo Agency Fleet Reviewerpipe-org/mcp-odoo | 421 | — | ~699 | Automated safety check: Pass | MIT |
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Works with
Categories
Retrieve market capitalization data for a single company using Octagon MCP. Company Market Cap is an agent skill from OctagonAI/skills. Retrieve market capitalization data for a single company using Octagon MCP.
Company Market Cap fits situations like: you need the current market value; valuation context; size classification for any publicly traded stock.
Run `npx skills add OctagonAI/skills --skill company-market-cap -a claude-code`. Or copy the skill folder (skills/company-market-cap in OctagonAI/skills) into .claude/skills/company-market-cap in your project. Claude Code loads it when a task matches its description.
Run `npx skills add OctagonAI/skills --skill company-market-cap -a codex`. Or copy the skill folder (skills/company-market-cap in OctagonAI/skills) into .agents/skills/company-market-cap in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OctagonAI/skills --skill company-market-cap -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/company-market-cap, .gemini/skills/company-market-cap, .github/skills/company-market-cap and .opencode/skills/company-market-cap in your project.
SKILL.md names no scripts, command-line tools or credentials: Company Market Cap is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Company Market Cap is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.5k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Company Market Cap: Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Okx Cex Market (dex-original/okx-agent-trade-kit, 110 stars), Polymarket Tennis (livetennisapi/livetennisapi-mcp, 152 stars) and Okx Sentiment Tracker (dex-original/okx-agent-trade-kit, 110 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
OctagonAI (a GitHub organization) maintains it in OctagonAI/skills, which has 127 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on June 5, 2026.
Source: OctagonAI/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.