Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Strategic BDI reasoning engine for autonomous AI agents with spatial utility and replanning.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"agent-reasoning": {
"command": "npx",
"args": [
"-y",
"@putervision/agent-reasoning-mcp"
]
}
}
}Run this in your terminal
claude mcp add agent-reasoning -- npx -y @putervision/agent-reasoning-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"agent-reasoning": {
"command": "npx",
"args": [
"-y",
"@putervision/agent-reasoning-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"agent-reasoning": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@putervision/agent-reasoning-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account putervision, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.4.1) reached the registry 34 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, SuperCollider
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
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Strategic BDI Reasoning, Multi-Attribute Expected Utility Theory & Decision Intelligence for Autonomous AI Agents
@putervision/agent-reasoning-mcp is a formal Model Context Protocol (MCP) server that provides strategic belief-desire-intention (BDI) reasoning, hierarchical goal decomposition, multi-attribute expected utility calculation (\(E[U] = \sum w_i u_i\)), exponential belief decay, quantitative risk evaluation, and reactive replanning across multi-modal memory bridges.
🌐 Official Documentation: putervision.com • Interactive Web Docs
# 1. Initialize reasoning database & seed default utility profiles
npx @putervision/agent-reasoning-mcp init
npx @putervision/agent-reasoning-mcp doctor
npx @putervision/agent-reasoning-mcp inspect
| Tool | Actions | Purpose |
|---|---|---|
set_goal | create, update, decompose, get, list, abandon | Manage goal hierarchy, task DAGs, and success criteria |
evaluate_situation | snapshot, quick | Score and rank candidate actions from environment snapshots |
replan | blocker, event, full | Adaptively reconstruct subgoals upon obstacles and abort stale intentions |
assess_risk | action, plan, compare | Quantitative threat and risk calculation across candidate actions |
query_knowledge | search, patterns, similar_situations | Search learned heuristics, tactical knowledge, and past decision patterns |
set_utility_weights | configure, get, list, activate | Configure utility weights (aggression, caution, greed, efficiency, exploration) |
get_decision_trace | latest, get, list, explain | Explainable chain-of-thought rationale and latency telemetry |
manage_beliefs | update, query, expire, reconcile | Structured belief state with exponential confidence decay ($C = C_0 e^{-\lambda t}$) |
manage_intentions | create, dispatch, get, list, cancel, resolve | Wire contract directives queue for runtime execution engines |
manage_reasoning_db | stats, audit, snapshot, restore | Reasoning database statistics, SHA-256 Merkle audit, and snapshot rollback |
Inspired by the typed System 1 pattern pioneered by TypeSafe's Jev (evaluating typed
Choice,Score, andNoulprimitives over compact state without token generation), implemented locally via in-memory LRU caches and deterministic heuristics (<2ms) without external API calls.
| Tool | Purpose | Latency Target | L1 Cache (p50) | Throughput |
|---|---|---|---|---|
classify | Low-latency categorical labeling over multi-modal StatePacks | <2ms | `0.0075 ms` | ~90,000 ops/s |
ask_noul | Typed probabilistic hypothesis and Boolean verification ($p \in [0.0, 1.0]$) | <2ms | `0.0049 ms` | ~127,000 ops/s |
ask_choice | Discrete $1$-of-$N$ choice selection ($N \le 16$) with probability simplex | <2ms | `0.0138 ms` | ~64,000 ops/s |
ask_score | Bounded numeric scalar scoring and calibrated utility rating | <2ms | `0.0057 ms` | ~129,000 ops/s |
gate_intention | Pre-dispatch blast-radius audit gate issuing signed HMAC dispatch tokens | <1ms | `0.0709 ms` | ~12,000 ops/s |
See [docs/benchmarks.md](docs/benchmarks.md) for full benchmark reproduction commands, latency percentiles (p50/p95/p99), and multi-tier caching architecture details.
agent-reasoning-mcp coordinates the closed-loop PuterVision Super-Loop:
init, doctor, inspect, run)..agent-reasoning-mcp.json parameters and environment variables.Add to .cursor/mcp.json or .vscode/mcp.json:
{
"mcpServers": { "agent-reasoning-mcp": { "command": "agent-reasoning-mcp", "args": ["run"], "env": { "PENTAD_HMAC_SECRET": "your-secure-shared-secret-here", "DISPATCH_TOKEN_TTL_MS": "30000" } } } }
PENTAD_HMAC_SECRET: 256-bit shared key for cryptographic intention dispatch token signing.DISPATCH_TOKEN_TTL_MS: Dispatch token expiration window (default: 30,000ms).SKIP_MODEL_LOAD: Set to 1 (or OFFLINE=1) to force air-gapped L1/L2 deterministic evaluation.# Run full unit and integration test suites
npm test
npm run benchmark
OFFLINE=1 SKIP_MODEL_LOAD=1 npm test
MIT © PuterVision