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MCP server · Agents

Agentic Aegis

Streaming validation engine for AI agents — real-time code validation during generation, shadow execution, protection layers. Rust core + MCP server.

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Scored 6 months ago · breakdown

About Agentic Aegis

Agentic Aegis is an MCP server in the Agents category: streaming validation engine for AI agents — real-time code validation during generation, shadow execution, protection layers. Rust core + MCP server.

Install

From source
git clone https://github.com/agentralabs/agentic-aegis

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (12)

aegis_check_inputCheck input for injection risks

Parameters not published.

aegis_check_outputCheck output for PII and safety

Parameters not published.

aegis_confidence_scoreScore code confidence

Parameters not published.

aegis_correction_hintGenerate correction suggestions

Parameters not published.

aegis_rollbackRollback to previous state

Parameters not published.

aegis_scan_securityFull security scan

Parameters not published.

aegis_session_createCreate validation session

Parameters not published.

aegis_session_endEnd validation session

Parameters not published.

aegis_session_statusGet session validation status

Parameters not published.

aegis_shadow_executeShadow-execute code in sandbox

Parameters not published.

aegis_validate_completeValidate complete code block

Parameters not published.

aegis_validate_streamingValidate code tokens in real time

Parameters not published.

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README


Sister in the Agentra ecosystem | .aegis format | 20 Capabilities | 12 MCP Tools | 30+ CLI Commands

Why AgenticAegis

Every AI agent ships code it has never validated. The generation finishes, the user runs it, and errors appear. Syntax mistakes. Type mismatches. Security vulnerabilities. Prompt injection payloads embedded in output. The validation happens after the damage -- if it happens at all.

The current fixes do not work. Linters run after generation -- they cannot catch errors mid-stream. Static analysis requires a complete file -- it cannot validate a partial token sequence. Security scanners are batch tools -- they cannot block a dangerous payload while it is still being written.

Current AI: Generates code first, validates later (if ever). AgenticAegis: Validates every token as it is generated -- syntax, types, security, and correctness are checked in real time, not after the fact.

AgenticAegis provides streaming validation -- a live shield that analyzes code as it is being generated. Not "lint your output." Your agent has a guardian -- token-level syntax validation, type flow tracking, shadow compilation, prompt injection detection, and PII scanning -- all running in parallel with generation.

Quickstart

cargo install agentic-aegis-cli
aegis --help

Problems Solved (Read This First)

  • Problem: generated code has syntax errors that are only discovered when the user tries to compile. Solved: streaming syntax validation catches malformed code while the LLM is still generating -- errors are flagged before the response completes.
  • Problem: type mismatches propagate silently through generated code. Solved: type flow tracking follows types across function boundaries during generation, flagging incompatible assignments before they reach the user.
  • Problem: LLM output can contain prompt injection payloads. Solved: prompt injection detection scans every token for injection patterns, blocking dangerous payloads during generation.
  • Problem: generated code may leak PII or sensitive data. Solved: PII detection and content filtering run on the output stream, catching sensitive data before it leaves the generation pipeline.
  • Problem: there is no way to undo a generation that went wrong. Solved: session management with rollback support lets the agent revert to a known-good state when validation fails.
  • Problem: validation confidence is binary -- pass or fail with no nuance. Solved: confidence scoring provides granular assessment of code quality, security risk, and correctness probability.
# Validate as you generate, protect as you ship -- three commands
aegis session create --language rust
aegis validate streaming --session <id> --input "fn main() { ... }"
aegis scan security --session <id>

Three commands. Real-time protection. Works with Claude, GPT, Ollama, or any LLM you switch to next.


How It Works

Architecture Overview

+-------------------------------------------------------------+
|                     YOUR AI AGENT                           |
|           (Claude, Cursor, Windsurf, Cody)                  |
+----------------------------+--------------------------------+
                             |
                  +----------v----------+
                  |      MCP LAYER      |
                  |   12 Tools + stdio  |
                  +----------+----------+
                             |
+----------------------------v--------------------------------+
|                    AEGIS ENGINE                              |
+-----------+-----------+------------+-----------+------------+
| Validators| Shadow    | Protection | Session   | Token      |
| (4 types) | Execution | Layers     | Manager   | Conservation|
+-----------+-----------+------------+-----------+------------+
                             |
                  +----------v----------+
                  |     .aegis FILE     |
                  |(validation session) |
                  +---------------------+

20 Capabilities

Tier Capabilities Focus
T1: Stream Validation Token Validator, Syntax Accumulator, Type Flow Tracker, Error Predictor Is the code well-formed?
T2: Shadow Execution Shadow Compiler, Sandbox Executor, Effect Tracker, Resource Monitor Does the code do what it claims?
T3: Input Protection Prompt Injection Detector, Intent Verifier, Payload Scanner, Rate Limiter Is the input safe?
T4: Output Protection Content Filter, PII Detector, Code Safety Analyzer, Output Sanitizer Is the output safe?
T5: Session Management Validation Session Manager, Correction Hint Generator, Confidence Scorer, Rollback Engine Can we recover from errors?

Full capability documentation ->


MCP Tools

Tool Description
aegis_validate_streaming Validate code tokens in real time
aegis_validate_complete Validate complete code block
aegis_shadow_execute Shadow-execute code in sandbox
aegis_check_input Check input for injection risks
aegis_check_output Check output for PII and safety
aegis_session_create Create validation session
aegis_session_status Get session validation status
aegis_session_end End validation session
aegis_correction_hint Generate correction suggestions
aegis_confidence_score Score code confidence
aegis_rollback Rollback to previous state
aegis_scan_security Full security scan

Benchmarks


Install

git clone https://github.com/agentralabs/agentic-aegis.git
cd agentic-aegis
cargo install --path crates/agentic-aegis-cli
curl -fsSL https://agentralabs.tech/install/aegis | bash
npm install @agenticamem/aegis

Standalone guarantee: AgenticAegis operates fully standalone. No other sister, external service, or orchestrator is required.


License

MIT -- see LICENSE.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Agentic Aegis

How do I install Agentic Aegis?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Agentic Aegis safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Agentic Aegis still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.