tzero-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | No | Google Gemini API key. Auto-detected and inherited from the system environment when present (optional; required only for AI provider mode). | |
| NVIDIA_API_KEY | No | NVIDIA NIM API key. Auto-detected and inherited from the system environment when present (optional; required only for AI provider mode). | |
| OPENAI_API_KEY | No | OpenAI API key. Auto-detected and inherited from the system environment when present (optional; required only for AI provider mode). | |
| ANTHROPIC_API_KEY | No | Anthropic API key. Auto-detected and inherited from the system environment when present (optional; required only for AI provider mode). | |
| OPENROUTER_API_KEY | No | OpenRouter API key. Auto-detected and inherited from the system environment when present (optional; required only for AI provider mode). | |
| TZERO_NO_AUTO_INSTALL | No | Set to 1 to opt out of the automatic dependency check/install that runs on startup. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_project_context_treeA | Scans the target project directory and builds an enterprise-grade multi-tier T-Zero hierarchical context tree (T-1 Master Architecture, T-2 Module References, T-3 AST Signatures, T-4 Agent Boundary Rules). Behavior:
Usage Guidelines:
Returns: Structured Markdown containing directory tree, module outlines, and AST signatures up to max_tokens. |
| query_module_dependenciesA | Analyzes import/export dependencies, module relationships, and internal vs external package dependencies across polyglot files (Python, TypeScript, Go, Rust, Java, C#, C++). Behavior:
Usage Guidelines:
Returns: Markdown report detailing inbound referrers, outbound imports, and the workspace dependency pool. |
| query_architecture_boundariesA | Retrieves active T-4 architectural tier boundary definitions, operational constraints, and zero-leak security rules defined in tzero.rules.json or built-in defaults. Behavior:
Usage Guidelines:
Returns: Markdown specification of architectural layers, allowed/forbidden import directions, and security constraints. |
| generate_architecture_blueprintA | Generates a complete system architectural specification (ARCHITECTURE.md) including auto-generated Mermaid component topology diagrams, layer boundaries, and module hierarchies. Behavior:
Usage Guidelines:
Returns: Comprehensive Markdown document with live Mermaid diagrams, layer classifications, and component interfaces. |
| generate_repo_mapA | Generates an ultra-compressed AST symbol token map (classes, methods, functions) tailored for LLM chat prompts and extreme context window savings. Behavior:
Usage Guidelines:
Returns: Compact Markdown symbol map indexed by file path. |
| audit_codebase_qualityA | Performs an AST static code smell audit, cyclomatic complexity check, copy-paste duplicity scan, and 100% Zero-Leak security audit for exposed credentials. Behavior:
Usage Guidelines:
Returns: Comprehensive diagnostic Markdown report with severity ratings (T-001 Security, T-002 Boundaries, T-003 Contracts, T-004 Complexity), line numbers, and actionable remediation steps. |
| find_code_duplicityA | Scans the repository to identify duplicate or copy-pasted blocks of code across multiple files to identify refactoring opportunities. Behavior:
Usage Guidelines:
Returns: Markdown report detailing duplicate code clusters with file paths, line ranges, and side-by-side code snippets. |
| estimate_token_costA | Calculates exact token count and estimated API prompting cost (USD) across major LLM providers (OpenAI GPT-4o, Claude 3.7 Sonnet, Groq, NVIDIA NIM, and Ollama $0) for a given text or directory. Behavior:
Usage Guidelines:
Returns: Markdown table comparing per-million token rates and total estimated costs across major models. |
| analyze_change_impactA | Calculates blast radius score (0-100) and identifies all direct and transitive dependent modules across the codebase before modifying a specific function, class, or symbol. Behavior:
Usage Guidelines:
Returns: Structured Markdown report with blast radius score, risk tier, direct dependents, and transitive impact paths. |
| enforce_architecture_boundariesA | Enforces T-4 architectural boundary rules (tzero.rules.json), verifying modular separation and detecting unauthorized cross-layer imports. Behavior:
Usage Guidelines:
Returns: Compliance report detailing pass/fail status, violating file paths, line numbers, layer names, and allowed import directions. |
| search_codebase_semanticA | 100% Private, local hybrid BM25 + TF-IDF semantic code search across workspace AST tokens, function headers, and docstrings without sending code to third-party embedding APIs. Behavior:
Usage Guidelines:
Returns: Ranked Markdown list of matching code snippets with file locations, match scores, and surrounding context. |
| export_agent_rulesA | Generates and writes standardized AI agent rule specifications (.cursorrules, .cursor/rules/*.mdc, .clinerules, and .github/copilot-instructions.md) into the workspace. Behavior:
Usage Guidelines:
Returns: Confirmation message listing all generated rule file paths. |
| get_token_savings_metricsA | Computes quantitative token compression metrics, reduction percentage, and developer team financial ROI savings (USD/month). Behavior:
Usage Guidelines:
Returns: Markdown executive summary with token reduction percentages, monthly developer cost savings, and annual ROI projections. |
| get_incremental_diff_contextA | Calculates hyper-compact PR git diff context (changed symbols + downstream blast radius dependents) for 98%+ token savings during code review and debugging. Behavior:
Usage Guidelines:
Returns: Structured Markdown diff context with changed symbol signatures, diff hunks, and caller references. |
| prune_code_snippetA | Compresses arbitrary in-memory source code or text into compact AST/interface signatures on-the-fly, returning pruned code and precise token savings percentage (80-95% reduction). Behavior:
Usage Guidelines:
Returns: Markdown fenced code block with pruned signatures and precise token reduction percentage. |
| verify_zero_leak_securityA | 100% Zero-Leak security scanner. Analyzes a file, code snippet, or repository workspace for hardcoded API keys (OpenAI, Anthropic, NVIDIA, Gemini, HuggingFace, GitHub), private keys, JWT tokens, and cloud secrets (100% private, 0 external network calls, $0 cost). Behavior:
Usage Guidelines:
Returns: Security pass/fail report with masked secret snippets, affected file paths, and line numbers. |
| verify_hallucination_guardA | Eliminates AI coding hallucinations before code is written or applied. Parses proposed code and verifies all internal imports and function/method call contracts (argument counts and keyword parameter names) against known workspace AST signatures. Behavior:
Usage Guidelines:
Returns: Verification status report with specific contract mismatches and 'did you mean' fuzzy suggestions. |
| get_smart_skeleton_contextA | Focus-aware dynamic skeletonizer. Returns the full, unpruned implementation of the focus file (or specific focus symbol), surrounded by ultra-compact T-3 AST signatures for all 1st-degree outbound imports and inbound callers. Solves the 'Lost in the Middle' problem while saving 95%+ tokens. Behavior:
Usage Guidelines:
Returns: Structured Markdown with full focus file source code and 1st-degree AST skeletons for imported and caller modules. |
| rank_repository_pagerankA | Identifies the architectural backbone and most critical modules of any repository using graph-theory PageRank centrality over AST import and reference topologies. Ranks modules by inbound/outbound degree and structural criticality. Behavior:
Usage Guidelines:
Returns: Ranked Markdown table with PageRank centrality scores, inbound/outbound degrees, and architectural significance notes. |
| trace_symbol_call_chainA | Traces deep execution paths across the codebase AST. Recursively discovers upstream callers (who calls symbol_name) and downstream callees (what symbol_name calls) up to max_depth, rendering an execution tree and Mermaid call diagram. Behavior:
Usage Guidelines:
Returns: Markdown report containing recursive ASCII execution tree, caller/callee counts, and copy-pasteable Mermaid flowchart syntax. |
| find_dead_codeA | Finds unused, orphaned, or unreferenced functions and classes across the codebase AST. Excludes all, main, dunder methods, and test functions. Behavior:
Usage Guidelines:
Returns: Markdown report listing candidate orphaned symbols with file paths, line numbers, and symbol types. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| tzero_grounding | Generates an architectural grounding prompt for AI coding agents. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Architecture Blueprint | Live Mermaid architecture blueprint and module topology for the workspace |
| Active Architectural Boundaries | Active T-4 architectural boundaries, Zero-Leak security rules, and constraints |
| Token ROI & Economic Savings | Quantitative token compression metrics and developer team ROI |
TDQS
Scored across 21 tools
Tools target distinct code-analysis operations (context generation, dependency graphs, architecture rules, quality audits, token metrics). Sibling Routing guidelines explicitly differentiate overlapping tools like get_project_context_tree vs get_smart_skeleton_context and analyze_change_impact vs trace_symbol_call_chain. However, several graph-analysis tools (query_module_dependencies, analyze_change_impact, trace_symbol_call_chain, rank_repository_pagerank) have adjacent scopes that could still cause occasional misselection.
All tool names are snake_case and follow a verb_noun structure (get_*, query_*, generate_*, audit_*, etc.). The specific verbs vary but are semantically appropriate and consistent, with no camelCase or chaotic style.
21 tools is in the heavy range (16-25) for a single server. Although each appears to serve a distinct sub-purpose, the set is large enough that discovery and selection may be cumbersome.
The surface covers major static-analysis workflows: context generation, dependency mapping, impact analysis, call tracing, architecture enforcement, security scanning, quality audits, and token metrics. Some gaps exist, such as no direct symbol-by-name lookup beyond semantic search or no runtime/test coverage analysis, but these are minor for the apparent read-only static-analysis domain.