



Network Working Group                                            G. Zeng
Internet-Draft                                                    J. Mao
Intended status: Informational                                    B. Liu
Expires: 6 May 2026                                              N. Geng
                                                                X. Shang
                                                                  Q. Gao
                                                                   Z. Li
                                                                  Huawei
                                                         2 November 2025


 Gap Analysis of Network Configuration Protocols in LLM-Driven Intent-
                            Based Networking
                  draft-zeng-opsawg-llm-netconf-gap-00

Abstract

   Large Language Models (LLMs) are entering network operations through
   natural-language intent interfaces.  Existing south-bound protocols
   (NETCONF, RESTCONF, gNMI, MCP, A2A) were not designed for
   conversational, semantically-rich, multi-agent orchestration.  This
   document provides a systematic gap analysis and identifies extension
   points for each protocol to meet intent-based networking
   requirements.

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   This Internet-Draft will expire on 6 May 2026.

Copyright Notice

   Copyright (c) 2025 IETF Trust and the persons identified as the
   document authors.  All rights reserved.





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   This document is subject to BCP 78 and the IETF Trust's Legal
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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Conventions and Definitions . . . . . . . . . . . . . . . . .   3
   3.  Gap Analysis per Protocol . . . . . . . . . . . . . . . . . .   3
     3.1.  MCP . . . . . . . . . . . . . . . . . . . . . . . . . . .   3
       3.1.1.  Gap Analysis  . . . . . . . . . . . . . . . . . . . .   3
       3.1.2.  Solution Considerations . . . . . . . . . . . . . . .   4
     3.2.  A2A . . . . . . . . . . . . . . . . . . . . . . . . . . .   5
       3.2.1.  Gap Analysis  . . . . . . . . . . . . . . . . . . . .   5
       3.2.2.  Solution Considerations . . . . . . . . . . . . . . .   7
     3.3.  NETCONF . . . . . . . . . . . . . . . . . . . . . . . . .   7
       3.3.1.  Gap Analysis  . . . . . . . . . . . . . . . . . . . .   7
       3.3.2.  Solution Considerations . . . . . . . . . . . . . . .   7
     3.4.  RESTCONF  . . . . . . . . . . . . . . . . . . . . . . . .   7
       3.4.1.  Gap Analysis  . . . . . . . . . . . . . . . . . . . .   7
       3.4.2.  Solution Considerations . . . . . . . . . . . . . . .   8
     3.5.  gNMI  . . . . . . . . . . . . . . . . . . . . . . . . . .   8
       3.5.1.  Gap Analysis  . . . . . . . . . . . . . . . . . . . .   8
       3.5.2.  Solution Considerations . . . . . . . . . . . . . . .   8
   4.  Summary . . . . . . . . . . . . . . . . . . . . . . . . . . .   8
   5.  Normative References  . . . . . . . . . . . . . . . . . . . .   8
   6.  Informative References  . . . . . . . . . . . . . . . . . . .   9
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   Intent-based networking (IBN) promises to translate high-level
   operator intent into network configuration without low-level syntax
   errors.  With the advent of LLMs, the interface moves from YAML/CLI
   to natural language.  Unfortunately, none of the current
   configuration or agent-to-agent protocols provide the semantic,
   transactional, and multi-agent primitives required by LLM-driven IBN.
   This draft analyses the gaps and proposes concrete extension
   directions for five widely deployed protocols.







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2.  Conventions and Definitions

   The key words "MUST", "MUST NOT", "REQUIRED", etc., are to be
   interpreted as described in [RFC2119].

   IBN, LLM, Agent, Intent, Tool, Artifact, and Task are used as defined
   in [I-D.ietf-opsawg-ibn-terminology].

3.  Gap Analysis per Protocol

3.1.  MCP

3.1.1.  Gap Analysis

   The design goal of MCP is to give a single Large Language Model (LLM)
   a "plug-and-play" tool-calling capability.  When deployed directly
   between a network controller and the devices, however, the following
   structural gaps are exposed.

3.1.1.1.  Lack of Network-Level Transaction Semantics

   MCP's tools/call is a stateless, one-shot JSON-RPC invocation.
   Network changes normally require the multi-stage semantics "candidate
   → validate → commit → rollback."  MCP has neither a candidate
   datastore nor two-phase-commit primitives.  Consequently, cross-
   device bulk deployments cannot guarantee "all-or-nothing" atomicity.
   When partial failures occur, the controller must supply its own
   compensation logic, lengthening the LLM's reasoning chain and
   increasing uncertainty.

3.1.1.2.  No YANG Semantics Discovery Mechanism

   Today MCP tool descriptors are written by hand.  Network-device
   capabilities are authoritatively defined by YANG models; whenever a
   model is updated, the tool list must be manually re-synchronized.
   Without an automated pipeline "YANG → JSON-Schema → tool descriptor,"
   maintaining the tool catalogue in a large multi-vendor environment
   becomes a bottleneck.

3.1.1.3.  Encoding and Bandwidth Bottlenecks

   Network-ops scenarios often involve high-frequency telemetry (5–60 s
   sampling, 10 k metrics per node).  MCP specifies only JSON-RPC over
   HTTP/1.1, resulting in highly redundant messages and no streaming
   push primitive.  When an LLM needs real-time anomaly detection,
   frequent polling consumes excessive bandwidth and CPU, violating
   data-center goals of low latency and high throughput.




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3.1.1.4.  Missing Multi-Device Context Correlation

   MCP's invocation context is confined to a single connection; it
   cannot natively carry network-level intent such as "change the same
   VLAN across three leaf switches while keeping the STP root bridge
   unchanged."  The LLM must repeat the constraints in the prompt,
   wasting tokens and raising the error rate.

3.1.1.5.  Lack of Network Rollback and Audit Hooks

   Network operations require audit logs that "trace down to the leaf
   node."  MCP's tool return body contains only a JSON result; there are
   no standardized fields for rollback-point, commit-id, or syslog-
   severity.  Root-cause analysis and compliance audits therefore
   require additional integration with device syslog or NETCONF logs,
   increasing cost.

3.1.1.6.  Incompatibility with Existing Device Security Models

   Devices commonly enforce certificate-based mutual-TLS plus NACM path-
   level permissions.  MCP currently defines only a Bearer-token header
   and offers no mapping between a tool call and the read/write/exec
   permissions on a YANG node.  If a tool-descriptor file leaks, an LLM
   could combine calls to bypass existing ACLs, creating a privilege-
   escalation risk.

3.1.1.7.  Lifecycle and State-Management Gap

   Network changes often last several minutes (waiting for BGP
   convergence or MAC migration).  Once an MCP call completes, its
   context is discarded immediately, so there is no way to stream
   intermediate updates such as “convergence 90 %.” The LLM has no
   choice but to poll repeatedly, increasing load on both itself and the
   device while still failing to achieve a true state-machine-driven
   closed loop.

3.1.2.  Solution Considerations

   For MCP to serve as "the universal glue between LLMs and devices" in
   production networks, an upper layer must supply a transactional state
   machine, a YANG self-description channel, streaming encodings, and
   fine-grained audit semantics.  Without these additions, MCP will
   remain confined to labs or single-device scripting and will be unable
   to close the loop on production-grade intent.







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3.2.  A2A

3.2.1.  Gap Analysis

   Positioned as a "multi-agent collaboration layer," the Agent-to-Agent
   (A2A) protocol was created so that any two LLM-Agents can discover
   each other, negotiate, and jointly finish long-running tasks.  When
   it is dropped straight into "network-controller ↔ network-device" or
   "controller ↔ controller" settings, however, the following deep gaps
   surface:

3.2.1.1.  Task Granularity Mismatch with Network Atomic Operations

   A2A Tasks target macro-level business goals (e.g., "relocate a DC").
   The smallest deliverable is an Artifact.  Network changes, by
   contrast, must touch a single YANG leaf (e.g., "set interface X MTU =
   9216").  The spec offers no "micro-task" primitive, so one Task
   either carries thousands of lines and becomes bloated, or is split
   into hundreds of Tasks that explode the state machine and raise LLM-
   orchestration complexity.

3.2.1.2.  No Network-Wide Transaction or Roll-back Semantics

   A2A's state machine is limited to pending → working → completed/
   failed.  On failure the controller only gets a free-text
   Task.statusMessage.  Network ops demand cross-device atomic commit
   plus a rollback tag.  The protocol today defines no:

   *  two-phase-commit token (transaction-id),

   *  distributed lock or conflict detection,

   *  unified rollback API (rollback-on-failure).

   Controllers must therefore implement compensation themselves, forcing
   the LLM to reason about "how to write a rollback script," which
   violates intent-based principles.

3.2.1.3.  Poor Encoding and Bandwidth Efficiency

   A2A mandates JSON for Artifact payloads and runs over HTTP/1.1.  For
   high-frequency telemetry (5 s interval, 10 k metrics/node) or bulk
   config pushes, JSON's textual redundancy causes:

   *  controller-device link congestion,

   *  wasted LLM-context tokens,




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   *  repetitive header parsing and higher CPU load.

   The protocol lacks a binary or streaming encoding option and offers
   no back-pressure mechanism.

3.2.1.4.  Missing Multi-Device Context Correlation

   A2A Task context is scoped to a single "conversation"; there is no
   standard field to express topology-level constraints such as "change
   the same VLAN on three leaf switches while keeping the STP root
   bridge unchanged."  The LLM must repeat inter-device relations in the
   prompt, burning tokens and risking truncation that produces
   configurations which are syntactically valid but topologically wrong.

3.2.1.5.  Incompatibility with Existing Device Security Models

   Devices generally enforce certificate-based mutual TLS plus NACM
   path-level access control.  A2A currently specifies only an OAuth2
   delegation token and provides no mapping from "Task-level role" to
   YANG node read/write/exec permissions, nor per-Artifact fine-grained
   ACLs.  Once an Artifact is cached or forwarded it may bypass the
   certificate chain, leading to privilege escalation or configuration
   pollution.

3.2.1.6.  No Network-Semantics Discovery Mechanism

   Skills are advertised in the Agent Card, but the Card is free text.
   There are no standard fields saying "I support OpenConfig BGP 4.0
   YANG" or "I manage AS 65001-65500."  LLMs must rely on fuzzy
   matching, often selecting the wrong partner and raising Task failure
   rates.

3.2.1.7.  Life-Cycle and Intermediate-State Reporting Gap

   Network changes can last minutes (waiting for BGP convergence, MAC
   moves).  After a Task enters "working," A2A only mandates a final
   Artifact; there is no standard way to push interim states such as
   "convergence 70 %" or "MTU changed, waiting for LLDP neighbor re-
   discovery."  The LLM must poll or wait until timeout, increasing load
   and preventing a true state-machine-driven closed loop.











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3.2.2.  Solution Considerations

   To act as a "multi-agent collaboration bus" in network environments,
   A2A must be systematically extended in task granularity, transaction
   semantics, binary encoding, topology context, security mapping, life-
   cycle management, and intermediate-state push.  Otherwise it will
   remain suited only for macro business flows and will be unable to
   close the fine-grained, reliable, and roll-backable network-intent
   loop required in production.

3.3.  NETCONF

3.3.1.  Gap Analysis

   NETCONF [RFC6241] provides transactional, XML-encoded RPCs over SSH.
   It lacks:

   *  Semantic discovery: YANG models are not self-describing for LLMs;
      no runtime tool list.

   *  Session context: no standard place to store intent-id, LLM prompt,
      or multi-device correlation.

   *  Streaming telemetry: <notification> is push-style but insufficient
      for high-frequency KPI.

   *  Function-level audit: <commit> is atomic, but per-leaf
      authorization is out-of-scope.

3.3.2.  Solution Considerations

   TBD

3.4.  RESTCONF

3.4.1.  Gap Analysis

   RESTCONF [RFC8040] maps YANG to HTTP URIs.  Gaps include:

   *  No candidate datastore—every PUT/PATCH is immediate.

   *  No server-side discovery document for LLMs.

   *  Stateless: no place to store multi-request intent.

   *  Encoding flexibility may confuse LLM prompt consistency.





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3.4.2.  Solution Considerations

   TBD

3.5.  gNMI

3.5.1.  Gap Analysis

   gNMI delivers high-speed telemetry but:

   *  No semantic metadata for LLMs.

   *  Set() is non-transactional across multiple paths.

   *  No multi-agent signalling—gNMI is 1:1.

   *  No standardized error ontology.

3.5.2.  Solution Considerations

   TBD

4.  Summary

   No single protocol satisfies all IBN-LLM requirements.
   NETCONF/RESTCONF/gNMI need semantic and transactional extensions;
   MCP/A2A need networking-specific profiling.  A companion document
   will define unified data models and security frameworks to close the
   identified gaps.

5.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", 1997.

   [RFC6241]  Enns, R., "Network Configuration Protocol (NETCONF)",
              2011.

   [RFC8040]  Bierman, A., "RESTCONF Protocol", 2017.

   [RFC9457]  Nottingham, M., "Problem Details for HTTP APIs", 2023.

   [OpenConfig-gNMI]
              Team, OpenConfig., "gNMI Specification", 2022.

   [MCP-spec] Inc, Anthropic., "Model Context Protocol", 2024.

   [A2A-spec] LLC, Google., "Agent-to-Agent Protocol", 2025.



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6.  Informative References

   [I-D.ietf-opsawg-ibn-terminology]
              IETF, "Intent-Based Networking Terminology", 2025.

Authors' Addresses

   Guanming Zeng
   Huawei
   Email: zengguanming@huawei.com


   Jianwei Mao
   Huawei
   Email: maojianwei@huawei.com


   Bing Liu
   Huawei
   Email: leo.liubing@huawei.com


   Nan Geng
   Huawei
   Email: gengnan@huawei.com


   Xiaotong Shang
   Huawei
   Email: shangxiaotong@huawei.com


   Qiangzhou Gao
   Huawei
   Email: gaoqiangzhou@huawei.com


   Zhenbin Li
   Huawei
   Email: robinli314@163.com











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