MCP vs Skill: A Decision Framework for AI Product Managers

1. Definitions: MCP and Skill

MCP (Atomic Tool/Interface) is a stable service interface for large models to call, corresponding to deterministic requirements, fixed logic, and single-step completion . Internal structure is stable and does not need dynamic adjustment. Examples: store subsidy query, product cost query, policy progress query — standardized for all merchants, returning results directly without additional model reasoning.

Skill (Orchestration Skill) chains multiple MCPs or tools into an action guide, equivalent to a flexible, modifiable enhanced workflow . It corresponds to complex requirements needing multi-step dynamic orchestration. Examples: generating customized business analysis reports or handling multi-step combined queries, where the model follows predefined steps.

In one sentence: MCP is the building block; Skill is the blueprint for assembling blocks.

2. How to Choose: MCP or Skill

The decision criterion is requirement certainty :

Requirement certain, process fixed → use MCP

Requirement dynamic, needs multi-step reasoning → use Skill

They are not mutually exclusive; apply per scenario. A key meeting principle: "If the process is certain to execute this way, tell it everything — don't let the model guess."

MCP invocation has two modes: hard-coded (intent recognition matches a specific MCP for fixed invocation) or semantic matching by the model. Outputs are standardized interface results requiring no further integration.

Skill invocation also has two modes: preset Skill (known fixed processes written into Skill, model invokes MCPs in sequence) and dynamic orchestration (model decomposes problems and orchestrates autonomously).

3. Technical Division of Labor

Division is clear: Business developers stabilize atomic capabilities; product managers and AI researchers co-create Skills. Product managers can deeply intervene in Skill descriptions and step clarity.

4. Integration Path for Existing Business

Recommended path: start from existing services/interfaces, combine with user scenarios to solve specific deterministic problems. Then encapsulate MCPs to address flexibility. Finally elevate to Skills to form standard processes.

One sentence: First make it run, then encapsulate, then orchestrate. Don't jump straight to Skills without a foundation.

5. Q&A for Product Managers and Non-Technical Colleagues

Q1: As a PM, how do MCP and Skill relate to me? Significantly. MCP function descriptions, user query corpora, and Skill step descriptions are all areas where PMs can intervene. Model tool selection largely depends on how clearly you write them.

Q2: Can Skill call MCP? Can it call ordinary APIs? Both. Can be written directly in skill.md or solidified as scripts. Skill is agnostic.

Q3: Must all existing business interfaces be wrapped as MCP? Only if directly called by the model. Interfaces not exposed to the model need not be forcibly wrapped — don't do MCP for MCP's sake.

Q4: With many MCPs and Skills, how does the model distinguish which to use? Through descriptions. The more accurate and clear the tool descriptions and Skill introductions, the better the model's judgment. This is the PM's responsibility.

Q5: How to handle compound questions (e.g., "check if an order enjoyed subsidy under a policy; if not, find the reason")? High-frequency common compound needs → make into Skill with explicit steps. Occasional, unforeseen needs → let the model decompose and call; if valuable after several runs, precipitate into Skill.

Q6: If v1 capabilities are all single-step, is MCP enough? Yes. v1 prioritizes MCP — low risk, fast landing. Build atomic capability foundation first, then iterate advanced Skills based on feedback.

Q7: What if user query matches both MCP and Skill? If fully delegated to model, it relies on description accuracy — whichever matches better wins. If using hard-coded intent recognition, recognition directly maps to fixed capability without model decision.

6. Key Takeaways

MCP is atomic tool — for deterministic needs, led by business R&D

Skill is orchestration skill — for dynamic complex needs, co-built by product + AI R&D

Selection based on requirement certainty — fixed process? Don't let the model guess

Landing path — run existing capabilities → encapsulate MCP → precipitate Skill

PM's battlefield — descriptions and process orchestration; this determines whether it runs accurately

AI capability building is fundamentally a layered activity: the foundation must be stable, the orchestration flexible. Hope this helps reduce deliberation in your next requirement review.