chimeralang-mcp 0.2.7

ChimeraLang MCP Server — probabilistic types, consensus gates, and hallucination detection as Claude tools

chimeralang-mcp

Give Claude typed confidence, hallucination detection, and constraint enforcement — as native MCP tools.

ChimeraLang is a programming language built for AI cognition. This MCP server exposes its runtime as 33 tools Claude can call during any conversation — no Anthropic permission needed, works today with Claude Desktop and Claude Code.

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Install

pip install chimeralang-mcp
# or
uvx chimeralang-mcp

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Claude Desktop Setup

Add to your config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "chimeralang": {
      "command": "uvx",
      "args": ["chimeralang-mcp"]
    }
  }
}

Or with pip-installed version:

{
  "mcpServers": {
    "chimeralang": {
      "command": "python",
      "args": ["-m", "chimeralang_mcp"]
    }
  }
}

Restart Claude Desktop — 33 ChimeraLang tools are now available.

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Tools

Core Language

Tool	What it does
chimera_run	Execute a .chimera program string
chimera_typecheck	Static type-check a .chimera program without executing
chimera_prove	Execute + generate a Merkle-chain integrity proof

Confidence & Safety

Tool	What it does
chimera_confident	Assert a value meets >= 0.95 confidence threshold
chimera_explore	Wrap a value as exploratory (hallucination explicitly permitted)
chimera_gate	Collapse multiple candidates via consensus (majority / weighted_vote / highest_confidence)
chimera_constrain	Full constraint middleware on any tool result
chimera_safety_check	Validate content against a safety policy
chimera_ethical_eval	Evaluate an action against ethical principles

Hallucination Detection

Tool	What it does
chimera_detect	Hallucination detection — 5 strategies: range, dictionary, semantic, cross_reference, temporal

Reasoning & Cognition

Tool	What it does
chimera_plan_goals	Decompose a high-level goal into ordered sub-goals
chimera_causal	Build and query a causal graph (add_edge / query / paths / info)
chimera_deliberate	Multi-perspective deliberation with Jaccard similarity and divergence scoring
chimera_quantum_vote	Multi-agent consensus voting with contradiction detection
chimera_metacognize	Reflect on reasoning quality — computes ECE, overconfidence rate
chimera_self_model	Maintain a persistent self-model of agent capabilities
chimera_embodied	Embodied reasoning simulation
chimera_social	Social reasoning and perspective modelling

Knowledge & Memory

Tool	What it does
chimera_world_model	Persistent in-session world model (key→value with confidence)
chimera_knowledge	In-session knowledge base (add / search / list)
chimera_memory	In-session memory store (store / recall by importance)

Token Budget & Cost

Tool	What it does
chimera_compress	Compress text using abbreviation/shorthand strategies
chimera_optimize	Aggressive text extraction (structural + entity + frequency)
chimera_fracture	Full pipeline — optimize docs + compress messages + quality gate
chimera_score	Rank messages by importance for lossy compression decisions
chimera_budget	Report current token usage against a budget
chimera_cost_estimate	Deterministic cost estimate for any supported model
chimera_cost_track	Record before/after compression events to the session tracker
chimera_dashboard	Session-level cost intelligence summary

Meta & Audit

Tool	What it does
chimera_audit	Session-level call log and confidence summary
chimera_evolve	Evolve and adapt reasoning strategies
chimera_meta_learn	Meta-learning across reasoning episodes
chimera_transfer_learn	Transfer learning across domains
chimera_fracture	Full compression pipeline with quality gate

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What problem does this solve?

Claude's tool-use loop has no built-in mechanism for:

• Confidence gating — only proceed if confidence >= threshold
• Typed output contracts — this result must satisfy constraint X before going downstream
• Genuine consensus detection — is multi-path agreement real, or trivially identical?
• Hallucination signals — structured detection, not just "does it sound right"
• Trust propagation — confidence degrades through chained tool calls; nothing tracks it
• Causal reasoning — explicit cause→effect graphs with pathway queries
• Multi-perspective deliberation — structured disagreement scoring across viewpoints
• Cost intelligence — token tracking and compression throughout long sessions

ChimeraLang fills exactly these gaps as a constraint layer sitting between Claude and its tools.

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Example prompts

Gate a value before a critical action:

"Before you submit that form, use chimera_confident to verify you're >= 0.95 confident the data is correct."

Consensus across reasoning paths:

"Generate 3 different answers, then use chimera_quantum_vote to collapse to the most reliable one."

Hallucination scan on output:

"After you get that search result, run chimera_detect with semantic strategy to check for absolute-certainty markers."

Full constraint pipeline:

"Use chimera_constrain on that tool result with min_confidence 0.85 and detect_strategy semantic."

Integrity proof for audit:

"Run this reasoning with chimera_prove so we have a tamper-evident trace."

End-to-end reasoning pipeline:

"Work through 'Should AI be used in autonomous medical diagnosis?' using chimera_plan_goals → chimera_causal → chimera_deliberate → chimera_quantum_vote → chimera_safety_check → chimera_ethical_eval → chimera_prove → chimera_audit."

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ChimeraLang Quick Reference

Variable Declaration

Both val and let are supported:

val answer = Confident("Paris", 0.97)
let hypothesis = Explore("maybe dark matter is...", 0.4)

Probabilistic Types

emit Confident("verified fact", 0.97)   // >= 0.95 required
emit Explore("hypothesis", 0.60)        // hallucination explicitly permitted

Assertions

assert Confident(0.78) > Confident(0.45)

Gate Declaration

gate verify(claim: Text) -> Converge<Text>
  branches: 3
  collapse: weighted_vote
  threshold: 0.80
  return claim
end

Logical Operators

Both keyword and symbolic forms are supported:

// keyword form
if a > 0.5 and b > 0.5
  emit Confident("both pass", 0.9)
end

// symbolic form (also valid)
if a > 0.5 && b > 0.5
  emit Confident("both pass", 0.9)
end

Hallucination Detection

detect temperature_check
  strategy: "range"
  on: temperature
  valid_range: [-50.0, 60.0]
  action: "flag"
end

If / Else

if confidence > 0.80
  emit Confident("high confidence result", 0.9)
else
  emit Explore("low confidence — needs review", 0.5)
end

For Loop

for item in items
  emit Explore(item, 0.6)
end

Match

match verdict
| "pass" => emit Confident("approved", 0.95)
| "fail" => emit Explore("rejected", 0.70)
| _      => emit Explore("unknown", 0.50)
end

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Changelog

0.2.6

• Fixed UnboundLocalError in chimera_cost_track caused by log variable shadowing the module-level logger in the chimera_audit handler
• Added let as a keyword alias for val in variable declarations
• Added && and || as lexer tokens (aliases for and / or)
• Expanded tool count to 33

0.2.5

• Initial AGI component suite: causal reasoning, deliberation engine, quantum vote, safety layer, ethical reasoner
• Knowledge base, world model, session memory
• Cost tracking, budget management, dashboard
• Self-model and metacognition tools

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Links

• ChimeraLang core: github.com/fernandogarzaaa/ChimeraLang
• OpenChimera: github.com/fernandogarzaaa/OpenChimera_v1

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License

MIT © Fernando Garza