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Strategic Agent Reasoning MCP

NPM · @PUTERVISION/AGENT-REASONING-MCP · SCANNED SEP 25

Strategic BDI reasoning engine for autonomous AI agents — goals, utility, and replanning.

+4 this week 75 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security96
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • No install/post-install scripts declared.Pass
  • 24 of 38 dependencies flagged as unhealthy (1 deprecated). View diagnostics → Partial
Provenance & Transparency48
  • Source repository is publicly reachable at the declared URL. View diagnostics → Pass
  • Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
  • Clear OSI-approved license (MIT).Pass
  • Actively maintained (last published 9 days ago).Pass
  • Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability80
  • 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
  • AI-judged instruction clarity (good).Pass
  • Tool/resource definitions use about 1600 tokens (~76/item across 21 items; 10 tools + 11 resources), lean.Pass
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management50
  • Stability observed for 15 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 10 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 11 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities20
  • Spec-recency check failed: implements MCP spec 2024-11-05; the latest is 2026-07-28. See how to fix → Fail
Install

How do I install the Strategic Agent Reasoning MCP server?

Strategic Agent Reasoning MCP runs locally as an npm package, launched with npx -y @putervision/agent-reasoning-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

npm · @putervision/agent-reasoning-mcp

# add to Claude Code
claude mcp add putervision-agent-reasoning-mcp -- npx -y @putervision/agent-reasoning-mcp
// .cursor/mcp.json
{
  "mcpServers": {
    "putervision-agent-reasoning-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@putervision/agent-reasoning-mcp"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "putervision-agent-reasoning-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@putervision/agent-reasoning-mcp"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add putervision-agent-reasoning-mcp -- npx -y @putervision/agent-reasoning-mcp
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "putervision-agent-reasoning-mcp": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@putervision/agent-reasoning-mcp"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add putervision-agent-reasoning-mcp --command npx --arg -y --arg @putervision/agent-reasoning-mcp
# ~/.hermes/config.yaml
mcp_servers:
  putervision-agent-reasoning-mcp:
    command: "npx"
    args: ["-y", "@putervision/agent-reasoning-mcp"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "putervision-agent-reasoning-mcp": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "@putervision/agent-reasoning-mcp"
      ]
    }
  }
}
# add to Vellum
assistant mcp add putervision-agent-reasoning-mcp -t stdio -c npx -a -y @putervision/agent-reasoning-mcp
// mcp.json
{
  "mcpServers": {
    "putervision-agent-reasoning-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@putervision/agent-reasoning-mcp"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 25 Sept 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 23 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 40 to 43. That category is still filling its 30-day observation window: 12 days of observed history at the previous scan, 13 at this one. The score rises as the window fills, whether or not the server changes.

  • 21 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.

  • 19 Sept 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 27 to 30. That category is still filling its 30-day observation window: 8 days of observed history at the previous scan, 9 at this one. The score rises as the window fills, whether or not the server changes.

  • 17 Sept 26 +16
    • Malware scan: unverified → pass ▲ security
  • 16 Sept 26 −12
    • Malware scan: pass → unverified ▼ security
    • Dependency health: 0.81 → 0.68 ▼ functional
    • Schema quality: 900 → 1600 ▼ functional
    • MCP protocol: pass → fail ▼ functional
    • Tool coverage: 0% → 100% ▲ functional
    • Stability: unverified → 0.20 ▲ functional
    • Schema quality: fair → good functional
    • Package version: 0.1.2 → 0.2.1 functional
  • 12 Sept 26 +15
    • Malware scan: unverified → pass ▲ security
  • 10 Sept 26 52

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 25 Sept 2026 · Analysed npm/@putervision/agent-reasoning-mcp@0.2.1

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem npm

Background: How many MCP packages publish verified provenance →

Dependencies 38 packages
Packages resolved 38
Deprecated 1
Stale 23
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 10 exposed · ~1,407 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
assess_risk ~94

Compute quantitative risk and threat assessment for candidate actions or plans against active utility weights.

NameTypeReqDescription
actionstringyesRisk assessment mode
candidate_actionstring–Action name to evaluate
candidate_actionsarray–Multiple actions to compare risk scores
parametersobject–Action parameters
projectstring–Target project slug
situation_contextobject–Current environment telemetry & vitals

No output schema declared.

No examples provided.

evaluate_situation ~179

Ingest multi-modal situation snapshot, compute expected utilities against active weights, and output prioritized action recommendations.

NameTypeReqDescription
actionstringyesSnapshot evaluation mode or quick text context
candidate_actionsarray–Candidate actions to score and rank
lookahead_depthnumber–Bounded heuristic lookahead plies (e.g. 2-3 plies, discount gamma=0.85)
projectstring–Target project slug
quick_contextstring–Text summary of current situation for quick evaluation
session_idstring–Linked state-memory session ID
snapshotobject–Normalized SituationSnapshot with world, vision, state, and vitals
trace_idstring–Distributed trace ID
utility_profilestring–Named utility profile to score against (defaults to active)

No output schema declared.

No examples provided.

get_decision_trace ~92

Retrieve explainable step-by-step chain-of-thought rationale, candidate utilities, and risk assessment for past decisions.

NameTypeReqDescription
actionstringyesTrace retrieval operation
goal_idstring–Filter traces by linked goal ID
limitnumber–Max traces to list
projectstring–Target project slug
trace_idstring–Trace ID for get/explain action

No output schema declared.

No examples provided.

manage_beliefs ~195

Maintain structured belief state with TTL expiration sweeps, exponential confidence decay, and category filtering.

NameTypeReqDescription
actionstringyesBelief operation
belief_idstring–Belief ID for specific lookup
categorystring–Belief category
client_request_idstring–Idempotency key
confidencenumber–Confidence score (0.0 to 1.0)
decay_ratenumber–Exponential decay rate lambda per hour
expires_atstring–ISO-8601 expiration timestamp
object––Belief value / state payload
predicatestring–Predicate relationship (e.g. "is_locked", "status")
projectstring–Target project slug
sourcestring–Belief provenance source
subjectstring–Belief subject (e.g. "north_gate", "enemy_patrol")

No output schema declared.

No examples provided.

manage_intentions ~205

Queue, dispatch, track, and resolve behavior directives (wire contract) for behavior-mcp.

NameTypeReqDescription
abort_conditionsarray–Auto-abort trigger conditions
actionstringyesIntention operation
behavior_namestring–Target behavior tree name (e.g. "combat_kite", "gather_loop")
client_request_idstring–Idempotency key
deadline_atstring–ISO-8601 completion deadline
goal_idstring–Linked goal ID
intention_idstring–Intention ID for dispatch/get/cancel/resolve
parametersobject–Runtime behavior parameters
prioritynumber–Execution priority (0.0 to 1.0)
projectstring–Target project slug
resultobject–Outcome payload for resolve action
statusstring–Status filter or update
trace_idstring–Linked decision trace ID

No output schema declared.

No examples provided.

manage_reasoning_db ~86

Database maintenance, stats, SHA-256 Merkle audit verification, checkpoints save/restore, and diffs.

NameTypeReqDescription
actionstringyesDatabase maintenance operation: stats, audit, doctor (health diagnostics), snapshot, diff, restore
descriptionstring–Description for snapshot
namestring–Snapshot name
projectstring–Target project slug

No output schema declared.

No examples provided.

query_knowledge ~90

Search learned heuristic patterns, tactics, and past decision traces by context similarity.

NameTypeReqDescription
actionstringyesKnowledge query mode
context_tagsarray–Filter by context tags
limitnumber–Max patterns to return
pattern_typestring–Filter by pattern category
projectstring–Target project slug
querystring–Semantic search query string

No output schema declared.

No examples provided.

replan ~105

Regenerate sub-task DAG and abort/recreate intentions upon unexpected blockers or environmental state changes.

NameTypeReqDescription
actionstringyesReplanning trigger type
blocker_descriptionstring–Description of the obstacle or blocker encountered
goal_idstringyesID of goal to replan
preserve_completedboolean–Whether to preserve already completed subgoals
projectstring–Target project slug
trigger_eventstring–Event description triggering replanning

No output schema declared.

No examples provided.

set_goal ~241

Register, update, decompose, or manage hierarchical goals and task DAGs in the reasoning engine.

NameTypeReqDescription
actionstringyesThe goal management operation to perform
client_request_idstring–Idempotency key to prevent duplicate creation
deadline_atstring–ISO-8601 deadline timestamp
descriptionstring–Detailed goal description
idstring–Goal ID (required for update, get, abandon)
limitnumber–Max items to return for list action
parent_idstring–Parent goal ID for hierarchical sub-goals
prioritynumber–Goal priority (0.0 to 1.0)
progressnumber–Completion progress (0.0 to 1.0)
projectstring–Target project slug
statusstring–Goal status
subgoalsarray–Array of sub-goals for decompose action
success_criteriaarray–List of verifiable conditions
titlestring–Goal title or objective summary
utility_weightsobject–Goal-specific utility weight overrides

No output schema declared.

No examples provided.

set_utility_weights ~120

Configure and activate multi-attribute utility weights (aggression, caution, greed, exploration, cooperation).

NameTypeReqDescription
actionstringyesProfile operation
descriptionstring–Profile description
is_activeboolean–Whether to set as currently active profile
namestring–Profile name (e.g. "aggressive", "cautious", "explorer")
projectstring–Target project slug
weightsobject–Key-value map of weight values (0.0 to 1.0)

No output schema declared.

No examples provided.

Common questions

What is the Strategic Agent Reasoning MCP server?

Strategic Agent Reasoning MCP is listed in the public MCP registry as io.github.putervision/agent-reasoning-mcp. Strategic BDI reasoning engine for autonomous AI agents, goals, utility, and replanning. This page covers its npm package (@putervision/agent-reasoning-mcp).

Is the Strategic Agent Reasoning MCP server safe to use?

Strategic Agent Reasoning MCP scores 75 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 25 September 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the Strategic Agent Reasoning MCP server expose?

Strategic Agent Reasoning MCP exposes 10 tools: set_goal, evaluate_situation, replan, assess_risk, query_knowledge, and 5 more. Their descriptions and schemas cost roughly 1,407 tokens of context every time the server is loaded.

Is the Strategic Agent Reasoning MCP server still maintained?

Strategic Agent Reasoning MCP is still listed as active in the MCP registry. We last reached this channel on 25 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the Strategic Agent Reasoning MCP server under?

Strategic Agent Reasoning MCP declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.