Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Adit-Jain-srm/skill-forge --skill mcp-conductorgit clone --depth 1 https://github.com/Adit-Jain-srm/skill-forgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/adit-jain-srm/skill-forge/mcp-conductor)<a href="https://agentmods.dev/skills/adit-jain-srm/skill-forge/mcp-conductor"><img src="https://agentmods.dev/badge/skills/adit-jain-srm/skill-forge/mcp-conductor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/adit-jain-srm/skill-forge/mcp-conductor"><img src="https://agentmods.dev/badge/skills/adit-jain-srm/skill-forge/mcp-conductor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.01432 |
| Opus 5 | $0.00045 | $0.00716 |
| Sonnet 5 | $0.00018 | $0.00286 |
| Haiku 4.5 | $0.00009 | $0.00143 |
Grade A, and why
mcp-conductor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Conductor — Multi-Server Orchestration
Overview
Teach your AI agent to orchestrate multiple MCP servers as a unified intelligence pipeline. Single MCP calls give shallow results. Chaining them gives 10x depth.
When to Use
- Task requires data from 2+ sources (search + scrape + analyze)
- User asks to "research" something (implies multi-source)
- Need to validate information across sources
- Building a comparison or competitive analysis
- Monitoring for changes over time
- Any workflow where one tool's output feeds another tool's input
Orchestration Patterns
Pattern 1: Research Pipeline
TASK: "Research how company X handles authentication"
Step 1: DISCOVER (Exa MCP)
→ web_search_exa: "company X authentication architecture blog"
→ Returns: 5-10 relevant URLs
Step 2: EXTRACT (Bright Data MCP)
→ scrape_as_markdown: each URL from Step 1
→ Returns: full page content as markdown
Step 3: ANALYZE (Agent reasoning)
→ Read all scraped content
→ Extract: patterns, technologies, trade-offs
→ Cross-reference findings
Step 4: ENRICH (GitHub MCP / gh CLI)
→ Search for open-source implementations mentioned
→ Read relevant source code for concrete examples
Step 5: SYNTHESIZE (Agent output)
→ Combine all sources into structured analysis
→ Cite sources, compare approaches, recommend
Pattern 2: Competitive Intelligence
TASK: "Compare all tools that solve X"
Step 1: SEARCH (Exa MCP — semantic search)
→ "tools libraries frameworks for X comparison 2026"
Step 2: VALIDATE (GitHub — verify repos exist and are active)
→ gh repo view each candidate — check stars, last push, activity
→ Filter: only repos pushed in last 90 days with 100+ stars
Step 3: DEEP-READ (Bright Data — get full documentation)
→ Scrape README, docs pages, getting-started guides
Step 4: ANALYZE (Agent — structured comparison)
→ Feature matrix, trade-offs, community health, performance claims
→ Output: ranked recommendation with evidence
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 159 lines · 90 tokens per session scan A ee926ffc0632
mcp-conductor is a skill published in the GitHub repository Adit-Jain-srm/skill-forge (2 stars, last pushed 2mo ago), licensed MIT. It adds 90 tokens to every session and 1,432 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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../../../../SKILL.md.
performance
You are running the Performance category of a Ship Score production readiness audit. Follow every instruction below precisely. Do not add checks beyond the 7 defined here. Do not skip checks. Report exactly what you find.