mcp-chaining

Q: How do I install mcp-chaining?

Run npx skills add https://github.com/parcadei/continuous-claude-v3 --skill mcp-chaining in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/mcp-chaining/ (personal) or .claude/skills/mcp-chaining/ (project).

by parcadeiAI & Agents

Research-to-implement pipeline chaining 5 MCP tools with graceful degradation

Installs: 481
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/parcadei/continuous-claude-v3 --skill mcp-chaining

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads mcp-chaining automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

MCP Chaining Pipeline

A research-to-implement pipeline that chains 5 MCP tools for end-to-end workflows.

When to Use

Building multi-tool MCP pipelines
Understanding how to chain MCP calls with graceful degradation
Debugging MCP environment variable issues
Learning the tool naming conventions for different MCP servers

What We Built

A pipeline that chains these tools:

Step	Server	Tool ID	Purpose
1	nia	`nia__search`	Search library documentation
2	ast-grep	`ast-grep__find_code`	Find AST code patterns
3	morph	`morph__warpgrep_codebase_search`	Fast codebase search
4	qlty	`qlty__qlty_check`	Code quality validation
5	git	`git__git_status`	Git operations

Key Files

scripts/research_implement_pipeline.py - Main pipeline implementation
scripts/test_research_pipeline.py - Test harness with isolated sandbox
workspace/pipeline-test/sample_code.py - Test sample code

Usage Examples

# Dry-run pipeline (preview plan without changes)
uv run python -m runtime.harness scripts/research_implement_pipeline.py \
    --topic "async error handling python" \
    --target-dir "./workspace/pipeline-test" \
    --dry-run --verbose

# Run tests
uv run python -m runtime.harness scripts/test_research_pipeline.py --test all

# View the pipeline script
cat scripts/research_implement_pipeline.py

Critical Fix: Environment Variables

The MCP SDK's get_default_environment() only includes basic vars (PATH, HOME, etc.), NOT os.environ. We fixed src/runtime/mcp_client.py to pass full environment:

# In _connect_stdio method:
full_env = {**os.environ, **(resolved_env or {})}

This ensures API keys from ~/.claude/.env reach subprocesses.

Graceful Degradation Pattern

Each tool is optional. If unavailable (disabled, no API key, etc.), the pipeline continues:

async def check_tool_available(tool_id: str) -> bool:
    """Check if an MCP tool is available."""
    server_name = tool_id.split("__")[0]
    server_config = manager._config.get_server(server_name)
    if not server_config or server_config.disabled:
        return False
    return True

# In step function:
if not await check_tool_available("nia__search"):
    return StepResult(status=StepStatus.SKIPPED, message="Nia not available")

Tool Name Reference

nia (Documentation Search)

nia__search              - Universal documentation search
nia__nia_research        - Research with sources
nia__nia_grep            - Grep-style doc search
nia__nia_explore         - Explore package structure

ast-grep (Structural Code Search)

ast-grep__find_code      - Find code by AST pattern
ast-grep__find_code_by_rule - Find by YAML rule
ast-grep__scan_code      - Scan with multiple patterns

morph (Fast Text Search + Edit)

morph__warpgrep_codebase_search  - 20x faster grep
morph__edit_file                 - Smart file editing

qlty (Code Quality)

qlty__qlty_check         - Run quality checks
qlty__qlty_fmt           - Auto-format code
qlty__qlty_metrics       - Get code metrics
qlty__smells             - Detect code smells

git (Version Control)

git__git_status          - Get repo status
git__git_diff            - Show differences
git__git_log             - View commit history
git__git_add             - Stage files

Pipeline Architecture

                    +----------------+
                    |   CLI Args     |
                    | (topic, dir)   |
                    +-------+--------+
                            |
                    +-------v--------+
                    | PipelineContext|
                    | (shared state) |
                    +-------+--------+
                            |
    +-------+-------+-------+-------+-------+
    |       |       |       |       |       |
+---v---+---v---+---v---+---v---+---v---+
| nia   |ast-grp| morph | qlty  | git   |
|search |pattern|search |check  |status |
+---+---+---+---+---+---+---+---+---+---+
    |       |       |       |       |
    +-------v-------v-------v-------+
                    |
            +-------v--------+
            | StepResult[]   |
            | (aggregated)   |
            +----------------+

Error Handling

The pipeline captures errors without failing the entire run:

try:
    result = await call_mcp_tool("nia__search", {"query": topic})
    return StepResult(status=StepStatus.SUCCESS, data=result)
except Exception as e:
    ctx.errors.append(f"nia: {e}")
    return StepResult(status=StepStatus.FAILED, error=str(e))

Creating Your Own Pipeline

Copy the pattern from scripts/research_implement_pipeline.py
Define your steps as async functions
Use check_tool_available() for graceful degradation
Chain results through PipelineContext
Aggregate with print_summary()

FAQ

What does the mcp-chaining skill do?

Research-to-implement pipeline chaining 5 MCP tools with graceful degradation

How do I install mcp-chaining?

Run npx skills add https://github.com/parcadei/continuous-claude-v3 --skill mcp-chaining in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/mcp-chaining/ (personal) or .claude/skills/mcp-chaining/ (project).

Which AI agents can use mcp-chaining?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is mcp-chaining safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains mcp-chaining?

It is published by parcadei in parcadei/continuous-claude-v3. It has 481 recorded installs.

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mcp-chaining

Install

Install

Describe the task

Review the result

SKILL.md

MCP Chaining Pipeline

When to Use

What We Built

Key Files

Usage Examples

Critical Fix: Environment Variables

Graceful Degradation Pattern

Tool Name Reference

nia (Documentation Search)

ast-grep (Structural Code Search)

morph (Fast Text Search + Edit)

qlty (Code Quality)

git (Version Control)

Pipeline Architecture

Error Handling

Creating Your Own Pipeline

FAQ

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