Agent skill

MCP Code Execution

by athola in athola/claude-night-market

Routes multi-tool workflows through MCP servers for large datasets and pipelines.

MITAuto-check passedAgent Workflows

Install MCP Code Execution

skills CLI
$ npx skills add athola/claude-night-market --skill mcp-code-execution -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install athola/claude-night-market mcp-code-execution --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/athola/claude-night-market.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/conserve/skills/mcp-code-execution .claude/skills/mcp-code-execution && rm -rf skills-src

Use ~/.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/

Facts

Skill name
mcp-code-execution
GitHub stars
342
Token cost
~2.1k tokens
SKILL.md length
688 words
Files
5
Skills in repo
159
Repo updated
First seen
Licence
MIT

At a glance

Routes multi-tool workflows through MCP servers for large datasets and pipelines.

  • Works in 4 steps: Assess Workflow… → Route to Modules… → Coordinate MECW… → …
  • Bash tool overhead is limiting throughput on data-heavy tasks
  • SKILL.md covers Quick Start, When To Use, When NOT To Use and Core Hub Responsibilities, plus 9 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

MCP Code Execution is an agent skill from athola/claude-night-market. Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `modules/mcp-coordination.md`, `modules/mcp-patterns.md` and `modules/mcp-subagents.md`).

It sits in Agent Workflows, covering MCP servers. It works with Model Context Protocol and Bash. The repository describes itself as: 23 Claude Code plugins: TDD enforcement hooks, git/PR workflows, spec-driven development, code review, project lifecycle, fix-from-error, maintenance automation, context… The licence is MIT.

When your agent uses it

  • Bash tool overhead is limiting throughput on data-heavy tasks
  • Tasks that involve MCP servers

Example prompts

  • “Use the mcp-code-execution skill to route multi-tool workflows through MCP servers for large datasets and pipelines”
  • “/mcp-code-execution”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Assess Workflow (mcp-code-execution:assess-workflow)
  2. Route to Modules (mcp-code-execution:route-to-modules)
  3. Coordinate MECW (mcp-code-execution:coordinate-mecw)
  4. Synthesize Results (mcp-code-execution:synthesize-results)

What it can do on your machine

Read from SKILL.md and the folder at commit 9f3eb00. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

MCP Code Execution loads about 2.1k tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 688 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from athola/claude-night-market at commit 9f3eb00, republished under its MIT licence (© athola). 688 words, ~2,059 tokens.

Download SKILL.mdSave it as .claude/skills/mcp-code-execution/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
mcp-code-execution
description
Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
alwaysApply
false
progressive_loading
true
dependencies.hub
context-optimization, token-conservation
dependencies.modules
mcp-subagents, mcp-patterns, mcp-validation
model_hint
standard

MCP Code Execution Hub

Quick Start

This skill is an orchestration hub, not a CLI. It activates inside a Claude Code session when one of the trigger keywords below appears, or when invoked explicitly:

Skill(conserve:mcp-code-execution)

The hub then routes to the relevant sub-skill modules (mcp-subagents, mcp-patterns, mcp-validation) based on the detected workflow shape. There is no separate install step or CLI entry point.

When To Use

  • Automatic: Keywords: code execution, MCP, tool chain, data pipeline, MECW
  • Tool Chains: >3 tools chained sequentially
  • Data Processing: Large datasets (>10k rows) or files (>50KB)
  • Context Pressure: Current usage >25% of total window (proactive context management)

MCP Tool Search (Claude Code 2.1.7+): When MCP tool descriptions exceed 10% of context, tools are automatically deferred and discovered via MCPSearch instead of being loaded upfront. This reduces token overhead by ~85% but means tools must be discovered on-demand. Haiku models do not support tool search. Configure threshold with ENABLE_TOOL_SEARCH=auto:N where N is the percentage.

Subagent MCP Access Fix (Claude Code 2.1.30+): SDK-provided MCP tools are now properly synced to subagents. Prior to 2.1.30, subagents could not access SDK-provided MCP tools: workflows delegating MCP tool usage to subagents were silently broken. No workarounds needed on 2.1.30+.

Claude.ai MCP Connectors (Claude Code 2.1.46+): Users logged into Claude Code with a claude.ai account may have additional MCP tools auto-loaded from claude.ai/settings/connectors. These tools contribute to the tool search threshold count. If workflows unexpectedly trigger tool search or context inflation, check /mcp for claude.ai-sourced connectors. Known reliability issue: connectors can silently disappear (GitHub #21817).

MCP Prompt Cache Fix (Claude Code 2.1.70+): MCP servers with instructions connecting after the first turn no longer bust the prompt cache. Previously, a late-connecting MCP server would invalidate cached prompt prefixes, increasing token costs for the rest of the session. On 2.1.70+, prompt cache reuse is preserved regardless of when MCP servers connect.

ToolSearch Reliability Fix (Claude Code 2.1.70+): Empty model responses after ToolSearch are fixed. The server was rendering tool schemas with system-prompt-style tags that could confuse models into stopping early. ToolSearch-heavy workflows (many deferred MCP tools) are now more reliable.

When NOT To Use

  • Simple tool calls that don't chain
  • Context pressure is low and tools are fast

Core Hub Responsibilities

  • Orchestrates MCP code execution workflow
  • Routes to appropriate specialized modules
  • Coordinates MECW compliance across submodules
  • Manages token budget allocation for submodules

Required TodoWrite Items

  1. mcp-code-execution:assess-workflow
  2. mcp-code-execution:route-to-modules
  3. mcp-code-execution:coordinate-mecw
  4. mcp-code-execution:synthesize-results

Step 1 – Assess Workflow (mcp-code-execution:assess-workflow)

Workflow Classification
python
def classify_workflow_for_mecw(workflow):
    """Determine appropriate MCP modules and MECW strategy"""

    if has_tool_chains(workflow) and workflow.complexity == "high":
        return {
            "modules": ["mcp-subagents", "mcp-patterns"],
            "mecw_strategy": "aggressive",
            "token_budget": 600,
        }
    elif workflow.data_size > "10k_rows":
        return {
            "modules": ["mcp-patterns", "mcp-validation"],
            "mecw_strategy": "moderate",
            "token_budget": 400,
        }
    else:
        return {
            "modules": ["mcp-patterns"],
            "mecw_strategy": "conservative",
            "token_budget": 200,
        }
MECW Risk Assessment

Delegate to mcp-validation module for detailed risk analysis:

python
def delegate_mecw_assessment(workflow):
    return mcp_validation_assess_mecw_risk(
        workflow, hub_allocated_tokens=self.token_budget * 0.5
    )
Show full SKILL.md (271 more words)Show less

Step 2 – Route to Modules (mcp-code-execution:route-to-modules)

Module Orchestration
python
class MCPExecutionHub:
    def __init__(self):
        self.modules = {
            "mcp-subagents": MCPSubagentsModule(),
            "mcp-patterns": MCPatternsModule(),
            "mcp-validation": MCPValidationModule(),
        }

    def execute_workflow(self, workflow, classification):
        results = []

        # Execute modules in optimal order
        for module_name in classification["modules"]:
            module = self.modules[module_name]
            result = module.execute(
                workflow,
                mecw_budget=classification["token_budget"]
                // len(classification["modules"]),
            )
            results.append(result)

        return self.synthesize_results(results)

Step 3 – Coordinate MECW (mcp-code-execution:coordinate-mecw)

Cross-Module MECW Management
  • Monitor total context usage across all modules
  • Enforce 50% context rule globally
  • Coordinate external state management
  • Implement MECW emergency protocols

Step 4 – Synthesize Results (mcp-code-execution:synthesize-results)

Result Integration
python
def synthesize_module_results(module_results):
    """Combine module results into a single status dict."""

    return {
        "status": "completed",
        "token_savings": calculate_savings(module_results),
        "mecw_compliance": verify_mecw_rules(module_results),
        "hallucination_risk": assess_hallucination_prevention(module_results),
        "results": consolidate_results(module_results),
    }

Module Integration

Available Modules
  • See modules/mcp-coordination.md for cross-module orchestration
  • See modules/mcp-patterns.md for common MCP execution patterns
  • See modules/mcp-subagents.md for subagent delegation strategies
  • See modules/mcp-validation.md for MECW compliance validation
With Context Optimization Hub
  • Receives high-level MECW strategy from context-optimization
  • Returns detailed execution metrics and compliance data
  • Coordinates token budget allocation
Performance Skills Integration
  • uses python-performance-optimization through mcp-patterns
  • Aligns with cpu-gpu-performance for resource-aware execution
  • validates optimizations maintain MECW compliance

Emergency Protocols

Hub-Level Emergency Response

When MECW limits exceeded:

  1. Delegates immediately to mcp-validation for risk assessment
  2. Route to mcp-subagents for further decomposition
  3. Apply compression through mcp-patterns
  4. Return minimal summary to preserve context

Success Metrics

  • Workflow Success Rate: >95% successful module coordination
  • MECW Compliance: 100% adherence to 50% context rule
  • Token Efficiency: Maintain >80% savings vs traditional methods
  • Module Coordination: <5% overhead for hub orchestration

Exit Criteria

  • Workflow classified into one of the three MECW strategies (aggressive/moderate/conservative) with the correct module roster (mcp-subagents, mcp-patterns, mcp-validation) selected based on tool-chain length and data size
  • Context usage remains at or below 50% of the total window throughout the workflow; any breach triggers the hub-level emergency response (delegate to mcp-validation, route to mcp-subagents, apply compression)
  • synthesize_module_results returns a dict with all four keys: status, token_savings, mecw_compliance, hallucination_risk
  • Token savings reported at the end of the workflow are greater than 80% compared to running the same workflow via direct Bash tool chaining

© athola, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files in plugins/conserve/skills/mcp-code-execution of athola/claude-night-market.

  • SKILL.md
  • modules/mcp-coordination.md
  • modules/mcp-patterns.md
  • modules/mcp-subagents.md
  • modules/mcp-validation.md

Open the folder on GitHubat commit 9f3eb00

Compare with similar skills

MCP Code Execution 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.

MCP Code Execution compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
MCP Code Execution this skillathola/claude-night-market342—~2.1kAutomated safety check: PassMIT
Crush Configurationcharmbracelet/crush29k—~3.7kAutomated safety check: PassCustom licence
Record Demoapify/mcpc983—~3.3kAutomated safety check: NotesApache-2.0
Releasejgravelle/jcodemunch-mcp2.7k—~6.5kAutomated safety check: PassCustom licence
Mcpcapify/mcpc983—~3.5kAutomated safety check: PassApache-2.0
Tool Selectiondatabricks-solutions/ai-dev-kit1.9k—~519Automated safety check: PassCustom licence

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Categories

Questions about MCP Code Execution

What does MCP Code Execution do?

Routes multi-tool workflows through MCP servers for large datasets and pipelines. MCP Code Execution is an agent skill from athola/claude-night-market. Routes multi-tool workflows through MCP servers for large datasets and pipelines.

When should I use MCP Code Execution?

MCP Code Execution fits situations like: bash tool overhead is limiting throughput on data-heavy tasks; tasks that involve MCP servers.

How do I install MCP Code Execution in Claude Code?

Run `npx skills add athola/claude-night-market --skill mcp-code-execution -a claude-code`. Or copy the skill folder (plugins/conserve/skills/mcp-code-execution in athola/claude-night-market) into .claude/skills/mcp-code-execution in your project. Claude Code loads it when a task matches its description.

How do I install MCP Code Execution in Codex?

Run `npx skills add athola/claude-night-market --skill mcp-code-execution -a codex`. Or copy the skill folder (plugins/conserve/skills/mcp-code-execution in athola/claude-night-market) into .agents/skills/mcp-code-execution in your project. Codex loads it when a task matches its description.

Can I use MCP Code Execution in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add athola/claude-night-market --skill mcp-code-execution -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mcp-code-execution, .gemini/skills/mcp-code-execution, .github/skills/mcp-code-execution and .opencode/skills/mcp-code-execution in your project.

What does MCP Code Execution need to run?

SKILL.md names no scripts, command-line tools or credentials: MCP Code Execution is instructions for the agent only. Our summary lists: Python 3.

Does MCP Code Execution access the network?

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.

Is MCP Code Execution safe to install?

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.

What licence does MCP Code Execution use?

MCP Code Execution is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does MCP Code Execution use?

About 2.1k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to MCP Code Execution?

Skills that share tags, products or a category with MCP Code Execution: Crush Configuration (charmbracelet/crush, 29k stars), Record Demo (apify/mcpc, 983 stars), Release (jgravelle/jcodemunch-mcp, 2.7k stars) and Mcpc (apify/mcpc, 983 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains MCP Code Execution?

athola (a GitHub user) maintains it in athola/claude-night-market, which has 342 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on October 6, 2026.

Source: athola/claude-night-market on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.