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MCP server · Agents

Grainulator

Research that compiles.

44Fair

Scored 4 months ago · breakdown

About Grainulator

Grainulator is an MCP server in the Agents category: research that compiles. It has been installed 0 times through Conduid.

Install

Clone
git clone https://github.com/grainulation/grainulator

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README


What it does

  • Multi-pass investigation — 3 research passes build evidence from different angles before synthesizing an answer
  • Typed claims, not vibes — every finding is tagged as factual, constraint, risk, recommendation, or estimate with an evidence tier (stated / web / documented / tested / production)
  • Tension detection — the compiler finds contradictions between claims and surfaces them before generating output
  • Confidence scoring — a 7-pass compiler grades evidence strength, type coverage, and bias to produce a 0-100 confidence score

Try the demo

grainulator.app runs a sprint in your browser. Type a question, watch three research passes execute, and see the compiled answer with claim breakdown.

What to expect from a single sprint:

Metric Typical value
Claims generated 12-16
Claim types 5 (factual, constraint, risk, recommendation, estimate)
Tensions detected 3-6
Evidence tiers web, documented, stated
Confidence score 63-68 / 100
Time to answer 40-70 seconds

The demo runs client-side to show the pipeline. The real tool (installed as a plugin) uses Claude for substantially higher quality research and deeper evidence.

Install

Step 1 — Add the marketplace (one-time):

claude plugin marketplace add https://github.com/grainulation/grainulator.git

Step 2 — Install:

claude plugin install grainulator

Inside Claude Code, use /plugin instead of claude plugin.

That's it. The plugin registers MCP servers, skills, hooks, and an autonomous agent.

Requirements: Claude Code with Node.js >= 20.

git clone https://github.com/grainulation/grainulator.git ~/.claude/plugins/grainulator
claude plugin add ~/.claude/plugins/grainulator

Commit to your project's .claude/settings.json:

{
  "enabledPlugins": ["grainulator@grainulation-marketplace"]
}

For air-gapped environments, use CLAUDE_CODE_PLUGIN_SEED_DIR with the plugin baked into container images.

Troubleshooting

MCP server disconnected / "tool not found". Claude Code's MCP registry occasionally drops stdio-connected servers (sleep, network hiccup, long-running session). Re-add the affected server:

claude mcp add wheat  -- npx -y -p @grainulation/wheat  wheat-mcp
claude mcp add mill   -- npx -y    @grainulation/mill   serve-mcp
claude mcp add silo   -- npx -y    @grainulation/silo   serve-mcp

Or run /healthcheck from any grainulator-enabled session to verify all three servers are responding and get the exact fix command for any that aren't.

Plugin commands not showing up. Restart Claude Code after claude plugin install — plugin registration is read at startup.

Permission prompts from hooks. Grainulator's hooks (pre-compile, post-claim) need .claude/settings.json permission. On first use Claude Code will prompt; allow, or pre-approve in your user or project settings.

How it works

You ask a question. Grainulator runs a research sprint.

The sprint has two phases:

1. Investigation (3 passes)

Each pass approaches the question from a different angle — constraints, risks, alternatives — and produces typed claims. Claims accumulate in claims.json, the sprint's evidence ledger.

2. Compilation (7 passes)

The compiler runs seven analysis passes over the collected claims:

  1. Type coverage — are there enough claim types to avoid blind spots?
  2. Evidence strength — are claims grounded in documentation, or just stated?
  3. Conflict detection — do any claims contradict each other?
  4. Bias scan — is the evidence skewed toward one conclusion?
  5. Gap analysis — what topics have thin coverage?
  6. Confidence scoring — weighted score from all the above
  7. Synthesis — final answer that acknowledges tensions and trade-offs

If unresolved conflicts exist, the compiler blocks output until you resolve them. The confidence score tells you how much to trust the answer.

Commands

Once installed, just talk to Claude. The intent router detects what you want.

Say this Grainulator runs
"research how our auth system works" Multi-pass research sprint
"challenge r003" Adversarial testing of claim r003
"what are we missing?" Blind spot analysis
"write it up" Compiled decision brief
"make slides" Presentation deck
"where are we?" Sprint status dashboard

Or use slash commands directly:

Command What it does
/init Start a new research sprint
/research Multi-pass investigation with evidence gathering
/challenge Adversarial testing of a specific claim
/witness Corroborate a claim against an external source
/blind-spot Structural gap analysis
/brief Compiled decision brief
/present Presentation deck
/status Sprint dashboard
/pull Import knowledge from DeepWiki or Confluence
/sync Publish artifacts to Confluence
/calibrate Score predictions against actual outcomes
/resolve Adjudicate conflicts between claims

Autonomous agent

The grainulator subagent runs full research sprints without intervention. It reads compiler output to decide what to do next — research, challenge, witness, blind-spot — until confidence is high enough for output.

Launch it: "research X using grainulator"

Architecture

grainulator/
  .claude-plugin/     Plugin manifest + permissions
  skills/             13 prompt-engineered workflows
  agents/             Autonomous sprint subagent
  hooks/              Auto-compile on claim mutation
  lib/                Shared utilities
  site/               grainulator.app landing page + demo

MCP servers: wheat (claims engine), mill (format conversion), silo (knowledge store), DeepWiki (codebase research)

Hooks: Auto-compile fires on every claim mutation. Write-guards protect claims.json and compilation.json from manual edits.

Orchard: Multi-sprint orchestration via orchard.json dependency graphs for complex investigations that span multiple questions.

The ecosystem

Grainulator is part of the grainulation ecosystem. Eight tools, each does one thing.

Tool What it does
wheat Research engine — structured evidence
farmer Permission dashboard — approve AI actions in real time
barn Shared tools — templates, validators, sprint detection
mill Format conversion — PDF, CSV, slides
silo Knowledge storage — reusable claim libraries
harvest Analytics — cross-sprint patterns
orchard Orchestration — multi-sprint coordination
grainulation Unified CLI — single entry point

You don't need all eight. /plugin install grainulator gives you everything you need.

Zero dependencies

Every grainulation tool runs on Node built-ins only. No npm install waterfall. No left-pad. No supply chain anxiety. MCP servers download on first use via npx.

Releases

See CHANGELOG.md for release history.

License

MIT

README mirrored from the source repository 4 months ago. The original is authoritative.

Questions

About Grainulator

How do I install Grainulator?

Run git clone https://github.com/grainulation/grainulator, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Grainulator safe to use with an AI agent?

Its trust score is 44 out of 100 (fair). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Grainulator still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.