io.github.chrbailey/promptspeak
Pre-execution governance for AI agents. Validates tool calls before they execute.
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promptspeak-mcp-server
Pre-execution governance for AI agents. Blocks dangerous tool calls before they execute.
AI agents call tools (file writes, API requests, shell commands) with no validation layer between intent and execution. A prompt injection, hallucinated argument, or drifting goal can trigger irreversible actions. PromptSpeak intercepts every MCP tool call, validates it against deterministic rules, and blocks or holds risky operations for human approval β in 0.1ms, before anything executes.

When to use this
- You run AI agents that call tools (MCP servers, function calling, tool use) and need a governance layer between the agent and the tools.
- You need human-in-the-loop approval for high-risk operations (production deployments, financial transactions, legal filings).
- You want to detect behavioral drift β an agent gradually shifting away from its assigned task.
- You need an audit trail of every tool call an agent attempted, whether it was allowed or blocked.
- You operate in a regulated domain (legal, financial, healthcare) where agent actions must be deterministically constrained.
Install
Claude Code
Add to ~/.claude/settings.json (or project-level .claude/settings.json):
{
"mcpServers": {
"promptspeak": {
"command": "npx",
"args": ["promptspeak-mcp-server"]
}
}
}
Restart Claude Code. All 56 governance tools are immediately available.
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"promptspeak": {
"command": "npx",
"args": ["promptspeak-mcp-server"]
}
}
}
As a library
npm install promptspeak-mcp-server
From source
git clone https://github.com/chrbailey/promptspeak-mcp-server.git
cd promptspeak-mcp-server
npm install && npm run build
npm start
Usage examples
1. Validate a governance frame
Validate that a PromptSpeak frame is structurally and semantically correct before using it. Frames encode governance constraints as symbol sequences β mode first, then domain, action, and entity.
// Tool call: ps_validate
{
"name": "ps_validate",
"arguments": {
"frame": "βββΆΞ±",
"validationLevel": "full"
}
}
// Response
{
"valid": true,
"frame": "βββΆΞ±",
"parsedFrame": {
"mode": { "symbol": "β", "meaning": "strict" },
"domain": { "symbol": "β", "meaning": "financial" },
"action": { "symbol": "βΆ", "meaning": "execute" },
"entity": { "symbol": "Ξ±", "meaning": "primary" }
},
"parseConfidence": 1.0,
"report": {
"valid": true,
"errors": [],
"warnings": [
{ "code": "ACTION_MISSING_DOMAIN", "message": "Consider adding domain context", "severity": "warning" }
]
},
"summary": { "errors": 0, "warnings": 1, "passed": 16 }
}
Invalid frames return actionable suggestions:
// Tool call: validate a frame with conflicting modes
{
"name": "ps_validate",
"arguments": { "frame": "βββΆ", "validationLevel": "semantic" }
}
// Response: blocked β strict + flexible modes conflict
{
"valid": false,
"summary": { "errors": 1, "warnings": 0, "passed": 10 },
"suggestions": ["Remove either β (strict) or β (flexible) - cannot have both"]
}
2. Hold queue workflow β human-in-the-loop approval
When an agent attempts a risky operation (high drift score, low confidence, security finding), the action is held for human review instead of executing. This is the full hold lifecycle: list, inspect, approve or reject.
Step 1: List pending holds
// Tool call: ps_hold_list
{
"name": "ps_hold_list",
"arguments": {}
}
// Response: one hold awaiting human review
{
"holds": [
{
"holdId": "hold_7k2m9x",
"agentId": "devops-agent",
"frame": "βββΆΞ±",
"tool": "deploy_to_production",
"severity": "high",
"reason": "drift_prediction",
"state": "pending",
"evidence": { "driftScore": 0.72, "predictedDrift": 0.85 }
}
],
"count": 1,
"expiredCount": 0
}
Step 2: Approve with modifications (or reject)
// Tool call: ps_hold_approve β approve but downgrade to staging
{
"name": "ps_hold_approve",
"arguments": {
"holdId": "hold_7k2m9x",
"reason": "Reviewed β safe for staging, not production",
"modifiedArgs": { "environment": "staging" }
}
}
// Response
{
"success": true,
"decision": {
"holdId": "hold_7k2m9x",
"state": "approved",
"decidedBy": "human",
"reason": "Reviewed β safe for staging, not production"
},
"executionResult": { "success": true }
}
To reject instead:
{
"name": "ps_hold_reject",
"arguments": {
"holdId": "hold_7k2m9x",
"reason": "Drift too high β recalibrate agent first",
"haltAgent": true
}
}
// Agent is halted (circuit breaker tripped) and the operation is denied.
3. Security scanning β catch vulnerabilities before execution
Scan code content for security issues before an agent writes it to disk. Critical findings block execution; high-severity findings are held for human review.
// Tool call: ps_security_scan
{
"name": "ps_security_scan",
"arguments": {
"content": "const query = `SELECT * FROM users WHERE id = ${userId}`;\nconst API_KEY = 'sk-1234567890abcdef1234567890abcdef';"
}
}
// Response: two findings β one critical (blocked), one critical (blocked)
{
"findings": [
{
"patternId": "sql-injection",
"severity": "critical",
"match": "SELECT * FROM users WHERE id = ${userId}",
"line": 1,
"context": "const query = `SELECT * FROM users WHERE id = ${userId}`;",
"suggestion": "Use parameterized queries or prepared statements instead of template literals"
},
{
"patternId": "hardcoded-secret",
"severity": "critical",
"match": "API_KEY = 'sk-1234567890abcdef1234567890abcdef'",
"line": 2,
"context": "const API_KEY = 'sk-1234567890abcdef1234567890abcdef';",
"suggestion": "Move secrets to environment variables or a secrets manager"
}
],
"scannedAt": "2026-03-19T12:00:00.000Z",
"contentLength": 98,
"patternsChecked": 10,
"enforcement": {
"blocked": [
{ "patternId": "sql-injection", "severity": "critical" },
{ "patternId": "hardcoded-secret", "severity": "critical" }
],
"held": [],
"warned": [],
"logged": []
}
}
Use ps_security_gate instead of ps_security_scan to enforce the policy β it blocks on critical, holds high-severity for human review, and warns on medium:
// Tool call: ps_security_gate β scan AND enforce
{
"name": "ps_security_gate",
"arguments": {
"content": "app.use(cors());\napp.listen(0.0.0.0, 3000);",
"action": "write_file"
}
}
// Response: held for review (insecure defaults = high severity)
{
"decision": "held",
"reason": "Security: 1 high-severity finding(s) held for review β insecure-defaults",
"scan": { "findings": [{ "patternId": "insecure-defaults", "severity": "high", "line": 1 }] }
}
How it works: 9-stage validation pipeline
Every tool call passes through this pipeline. If any stage fails, execution is blocked.
Agent calls tool
β
ββ 1. Circuit Breaker ββββ Halted agents blocked instantly (no further checks)
ββ 2. Frame Validation βββ Structural, semantic, and chain rule checks
ββ 3. Drift Prediction βββ Pre-flight behavioral anomaly detection
ββ 4. Hold Check ββββββββββ Risky operations held for human approval
ββ 5. Interceptor βββββββββ Final permission gate (confidence thresholds)
ββ 6. Security Scan βββββββ Scans write actions for vulnerabilities (see below)
ββ 7. Tool Execution ββββββ Only reached if all 6 pre-checks pass
ββ 8. Post-Audit ββββββββββ Confirms behavior matched prediction
ββ 9. Immediate Action ββββ Halts agent if critical drift detected post-execution
Stages 1-6 are pre-execution β the tool never runs if any check fails. Stages 8-9 are post-execution β they detect drift and can halt the agent for future calls.
Security scanning
When an agent writes code (write_file, edit_file, create_file, patch_file), the content is scanned against 10 detection patterns before execution. Severity determines enforcement:
| Severity | Enforcement | What it catches |
|---|---|---|
| CRITICAL | Blocked β execution denied | SQL injection via template literals, hardcoded API keys/passwords/tokens |
| HIGH | Held β queued for human review | Security-related TODOs, logging sensitive data, insecure defaults (cors(), 0.0.0.0, debug: true) |
| MEDIUM | Warned β logged, execution continues | Empty catch blocks, hedging comments ("probably works"), disabled tests |
| LOW | Logged β no enforcement | DROP TABLE, rm -rf (flagged for awareness) |
What works (tested)
All claims below are backed by passing tests (104 tests across 5 test files):
- Pattern detection works. Each of the 10 patterns is tested for true positives AND false positives. Example:
api_key = "sk-1234567890abcdef"is caught;API_KEY = process.env.API_KEYis not. SQL injection catches\SELECT * FROM users WHERE id = ${id}`but not parameterized queries (db.query("SELECT * FROM users WHERE id = ?", [id])`). - Severity enforcement works. Critical findings block execution. High findings hold for review. Medium findings warn but allow. Tested end-to-end through the interceptor pipeline.
- Only write actions are scanned.
read_fileand other non-write actions pass through without scanning, even if their arguments contain vulnerable code. Tested. - Runtime configuration works. Patterns can be enabled/disabled and severity can be changed at runtime via
ps_security_config. A disabled pattern stops firing immediately. Changing a pattern from medium to critical makes it block instead of warn. Tested end-to-end. - Performance is fine. 100-line file scans complete in under 10ms. Tested.
- Multiple findings in one file work. A file with 6 different vulnerability types correctly classifies each into the right severity bucket. Tested.
What does NOT work yet
No hold queue integration for HIGH findings.FIXED. HIGH-severity security findings now create real holds in HoldManager viasecurity_findingHoldReason. They appear inps_hold_listand can be approved/rejected through the normal hold flow.- No auto-scan on
ps_execute. The security scan only triggers in the interceptor'sintercept()method for direct tool calls. If an agent usesps_execute(the governed execution path), the scan runs only if the inner tool is a write action AND the content is passed as a top-level arg. Nested argument structures may bypass scanning. Why:ps_executewraps tool calls in its own argument schema; the scanner checksproposedArgs.content, not deeply nested fields. - No file-path-based scanning. The scanner only examines content passed as arguments. It cannot scan files already on disk β it doesn't read from the filesystem. Why: The scanner is a pure function that takes a string. Adding filesystem access would change the security model.
- Patterns are regex-based, not AST-aware. The patterns use regular expressions, which means they can't understand code structure. A hardcoded secret inside a test fixture or a SQL injection in a comment will still trigger. False positive rates range from 25-70% depending on the pattern (documented per-pattern). Why: AST parsing would add dependencies and complexity. Regex is fast and good enough for a governance layer that holds for human review rather than silently blocking.
- Partial persistence. Holds and circuit breaker state now persist to SQLite (
data/governance.db) and survive server restarts. However, pattern configuration changes (enable/disable, severity changes viaps_security_config) are still in-memory only and reset on restart. Why: Pattern config is lightweight and rarely changed; full config persistence would need a separate config store.
MCP tools (56)
Core governance
| Tool | When to call it | What it does |
|---|---|---|
ps_validate | Before executing any agent action | Validate a frame against all rules without executing |
ps_validate_batch | When checking multiple actions at once | Batch validation for efficiency |
ps_execute | When an agent wants to perform a tool call | Full pipeline: validate β hold check β execute β audit |
ps_execute_dry_run | When previewing what would happen | Run full pipeline without executing the tool |
Human-in-the-loop holds
| Tool | When to call it | What it does |
|---|---|---|
ps_hold_list | When reviewing pending agent actions | List all operations awaiting human approval |
ps_hold_approve | When a held operation should proceed | Approve with optional modified arguments |
ps_hold_reject | When a held operation should be denied | Reject with reason |
ps_hold_config | When tuning which operations require approval | Configure hold triggers and thresholds |
ps_hold_stats | When monitoring hold queue health | Hold queue statistics |
Agent lifecycle
| Tool | When to call it | What it does |
|---|---|---|
ps_state_get | When checking what an agent is doing | Get agent's active frame and last action |
ps_state_system | When monitoring overall system health | System-wide statistics |
ps_state_halt | When an agent must be stopped immediately | Trip circuit breaker β blocks all future calls |
ps_state_resume | When a halted agent should be allowed to continue | Reset circuit breaker |
ps_state_reset | When clearing agent state | Full state reset |
ps_state_drift_history | When investigating behavioral changes | Drift detection alert history |
Delegation
| Tool | When to call it | What it does |
|---|---|---|
ps_delegate | When an agent spawns a sub-agent | Create parentβchild delegation with constrained permissions |
ps_delegate_revoke | When revoking a sub-agent's authority | Remove delegation |
ps_delegate_list | When auditing delegation chains | List active delegations |
Configuration
| Tool | When to call it | What it does |
|---|---|---|
ps_config_set | When changing governance rules at runtime | Set configuration key-value pairs |
ps_config_get | When reading current configuration | Get current config |
ps_config_activate | When switching policy profiles | Activate a named configuration |
ps_config_export | When backing up configuration | Export full config as JSON |
ps_config_import | When restoring configuration | Import config from JSON |
ps_confidence_set | When tuning validation strictness | Set confidence thresholds |
ps_confidence_get | When checking current thresholds | Get current thresholds |
ps_confidence_bulk_set | When reconfiguring multiple thresholds | Batch threshold update |
ps_feature_set | When toggling pipeline stages | Enable/disable specific checks |
ps_feature_get | When checking which stages are active | Get feature flags |
Symbol registry (entity tracking)
| Tool | When to call it | What it does |
|---|---|---|
ps_symbol_create | When registering a new entity (company, person, system) | Create symbol with type, metadata, and tags |
ps_symbol_get | When looking up an entity | Retrieve by ID |
ps_symbol_update | When entity data changes | Update metadata or tags |
ps_symbol_list | When browsing entities by type | List with optional type filter |
ps_symbol_delete | When removing an entity | Delete by ID |
ps_symbol_import | When bulk-loading entities | Batch import |
ps_symbol_stats | When monitoring registry health | Registry statistics |
ps_symbol_format | When displaying an entity | Format symbol for display |
ps_symbol_verify | When confirming entity data is current | Mark symbol as verified |
ps_symbol_list_unverified | When auditing stale data | List symbols needing verification |
ps_symbol_add_alternative | When an entity has aliases | Add alternative identifier |
Security enforcement
| Tool | When to call it | What it does |
|---|---|---|
ps_security_scan | When checking code for vulnerabilities | Scan content, return findings by severity |
ps_security_gate | When enforcing security policy on writes | Scan + enforce: block/hold/warn/allow |
ps_security_config | When tuning detection patterns | List, enable, disable, change severity of patterns |
Audit
| Tool | When to call it | What it does |
|---|---|---|
ps_audit_get | When reviewing what happened | Full audit trail with filters |
Architecture
src/
βββ gatekeeper/ # 8-stage validation pipeline (core enforcement)
β βββ index.ts # Pipeline orchestrator + agent eviction policy
β βββ validator.ts # Frame structural/semantic/chain validation
β βββ interceptor.ts# Permission gate with confidence thresholds
β βββ hold-manager.ts# Human-in-the-loop hold queue
β βββ resolver.ts # Frame resolution with operator overrides
β βββ coverage.ts # Coverage confidence calculator
βββ drift/ # Behavioral drift detection
β βββ circuit-breaker.ts # Per-agent halt/resume
β βββ baseline.ts # Behavioral baseline comparison
β βββ tripwire.ts # Anomaly tripwires
β βββ monitor.ts # Continuous monitoring
βββ security/ # Security vulnerability scanning
β βββ patterns.ts # 10 detection patterns (regex-based)
β βββ scanner.ts # Scanner engine + severity classification
βββ persistence/ # SQLite governance persistence
β βββ database.ts # Holds, decisions, circuit breakers (WAL mode)
βββ symbols/ # SQLite-backed entity registry (11 CRUD tools)
βββ policies/ # Policy file loader + overlay system
βββ operator/ # Operator configuration
βββ tools/ # MCP tool implementations
β βββ registry.ts # 29 core tools
β βββ ps_hold.ts # 5 hold tools
β βββ ps_security.ts# 3 security tools
βββ handlers/ # Tool dispatch + metadata registry
βββ core/ # Logging, errors, result patterns
βββ server.ts # MCP server entry point (stdio transport)
Performance
PromptSpeak adds governance to every tool call with sub-millisecond overhead. Benchmarked on Apple M2 Pro, Node.js 22, Vitest 4.0:
Latency (pre-execution check, 1000 iterations)
| Percentile | Latency |
|---|---|
| Average | 0.164ms |
| P95 | 0.368ms |
| P99 | 1.183ms |
| Full execution path P95 | 0.074ms |
Throughput (concurrent operations)
| Operation | Rate |
|---|---|
| Circuit breaker checks (1000 concurrent) | 6,173 ops/sec |
| Hold creation | 55,556 holds/sec |
| Hold approval/rejection | 200,000+/sec |
| Mixed operations (halt + hold + allow) | 6,818 ops/sec |
Stress Tests
| Test | Result |
|---|---|
| 1000 concurrent blocked executions | 162ms total, all blocked correctly |
| 100 rapid halt/resume cycles | 100% correct state transitions |
| 500 agents with mixed states | 250 blocked, 250 allowed β zero misclassification |
| Memory under sustained load (1000 ops) | Negative delta (-11.76 MB, GC reclaimed) |
Suite
| Metric | Value |
|---|---|
| Test count | 829 tests across 33 files |
| Test duration | 1.11s total |
| Categories | Unit, integration, stress, security, grammar |
Requirements
- Node.js >= 20.0.0
- TypeScript 5.3+ (build from source)
- No external services required β SQLite for symbols and governance persistence
Related Projects
- deeptrend β Structured AI trend feed for autonomous agents. Curated from 14+ sources, synthesized via LLM Counsel, published every 6h as JSON Feed, RSS, and
llms.txt. Designed as a data source for agent monitoring pipelines.
Privacy Policy
https://promptspeak.admin-as-a-service.com/privacy
PromptSpeak does not collect personal data, has no telemetry, and stores all governance data locally in SQLite. See the full policy at the link above.
Data Processing Terms
https://promptspeak.admin-as-a-service.com/dpa
Standard data processing terms for platform integrations (e.g., Anthropic Connectors). PromptSpeak acts as a data processor; no sub-processors, no external data transmission.
License
MIT
